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spectral analysis | When to use symmetric vs asymmetric (periodic) window functions? | https://dsp.stackexchange.com/questions/95448/when-to-use-symmetric-vs-asymmetric-periodic-window-functions | <p>Libraries like <a href="https://docs.scipy.org/doc/scipy/reference/signal.windows.html" rel="nofollow noreferrer">scipy</a> typically offer constructing window functions in a symmetric or asymmetric flavor. I'm aware of the rule of thumb:</p>
<ul>
<li>Use symmetric for filter analysis.</li>
<li>Use asymmetric for sp... | <p>It’s <em>very</em> nitpicky, but I’m assuming it has to do with the following considerations:</p>
<ul>
<li><p>The <em>window method</em> for filter design consists in windowing an ideal infinite duration filter (such as a <span class="math-container">$\tt{sinc}$</span>) to make it realizable. Most of the time, line... | 534 |
spectral analysis | Can spectral density be a complex quantity? | https://dsp.stackexchange.com/questions/54573/can-spectral-density-be-a-complex-quantity | <p>I have a signal (<span class="math-container">$S(t)$</span>) which is product of a Gaussian (<span class="math-container">$G(t)$</span>) and a random phase function (<span class="math-container">$e^{i\theta(t)}$</span>, here <span class="math-container">$\theta(t)$</span> is a random function), as shown below</p>
<... | <blockquote>
<p>and the same goes with the spectral density (Fourier transform of the auto-correlation function). </p>
</blockquote>
<p>No, that's not the case.</p>
<p>Since the autocorrelation is a hermitian symmetric function for <em>any</em> <span class="math-container">$S$</span>, its Fourier transform is alway... | 535 |
spectral analysis | What is the best way to represent audio visually? (x-post from UX) | https://dsp.stackexchange.com/questions/2744/what-is-the-best-way-to-represent-audio-visually-x-post-from-ux | <p>Original Question: <a href="https://ux.stackexchange.com/q/23040/16006">https://ux.stackexchange.com/q/23040/16006</a></p>
<p>I've only taken some basic signal analysis courses, so I might be missing some things.</p>
<p><strong>Purely theoretical question:</strong></p>
<p>What methods exist for representing audio... | <p>What a human (or their ear-brain) perceives in sound is a psychoacoustic phenomena, and may or may not be exactly related to the actual audio as recorded. e.g. the exact notes, beats and instruments that a human "hears" may be influenced by visual cues, memory of other similar music, and the musical context around ... | 536 |
spectral analysis | Spectral entropy and moments and non stationary signal processing | https://dsp.stackexchange.com/questions/49809/spectral-entropy-and-moments-and-non-stationary-signal-processing | <p>What is Spectral entropy and spectral moments? I know what the normal entropy of a signal is! And also what are some good time-frequency features for the analysis of non-stationary signals?</p>
| 537 | |
spectral analysis | hamming window for LPC | https://dsp.stackexchange.com/questions/25747/hamming-window-for-lpc | <p>I am working on a library for generating LPC for speech synthesis. I am currently using a hamming window for the spectral analysis which goes in 200ms blocks over the signal, and does the a-to-k conversion.</p>
<p>I have read some stuff online about a technique of overlapping these windows so it would process the ... | 538 | |
spectral analysis | FFT freqency bin center in R | https://dsp.stackexchange.com/questions/61029/fft-freqency-bin-center-in-r | <p>I'm trying to do a spectral analysis in R. I learned it in Python from Allen Downey's ThinkDSP book.</p>
<p>What is the R equivalent of the Python numpy function, numpy.fft.fftfreq?</p>
<p>If you provide a window length and spacing, that function returns the frequency bin centers. I've been hunting through R packa... | 539 | |
spectral analysis | Using Fast Fourier Transform to determine musical notes | https://dsp.stackexchange.com/questions/54072/using-fast-fourier-transform-to-determine-musical-notes | <p>Hi guys i am doing a course in Digital Filters and Spectral analysis. We are given a coursework/homework, and I have absolutely no idea what to do with it. I come from Maths background, never done any signal processing before, and since I am new to the university I don't really have anyone to ask.</p>
<p>Problem:</... | <p>As Robert B.J. has already indicated, a bare bones FFT analysis is not the recommended method for a professional audio harmonic inspection. Nevertheless it can be very useful in certain cases, one of which is, I think, this one. Be aslo warned that, as hotpaw2 indicated, with this simplistic approach, false positive... | 540 |
spectral analysis | Spectral centroid manipulations | https://dsp.stackexchange.com/questions/42452/spectral-centroid-manipulations | <p>So, I've created a simple sound analysis application and one of the features I've implemented is the spectral centroid (as explained here <a href="https://en.wikipedia.org/wiki/Spectral_centroid" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Spectral_centroid</a>). In order to get reliable results, we need... | <p>It's been some time since I asked this question and after some work done on this subject, I think it's time to revisit it. It should be noted that
while the spectral centroid, pretty much like any other spectral feature, is calculated using the FFT magnitudes, and not raw FFT data, we don't
have to manipulate the m... | 541 |
spectral analysis | Signal Plus Weakly Stationary Noise | https://dsp.stackexchange.com/questions/17698/signal-plus-weakly-stationary-noise | <p>I was reading the book "Spectral Analysis of Time Series" By Herman Koopmans.
On <a href="http://books.google.de/books?id=F09lhyXw4mcC&lpg=PP1&dq=herman%20koopman%20time%20series&pg=PA55#v=onepage&q=A%20Nonstationary%20Process%20with%20a%20Wiener%20Spectrum&f=false" rel="nofollow">Page 55</a>, he... | <p>For ergodic processes, time averages (defined by integrals over time) and ensemble averages (defined by expectations with respect to probability distributions) are identical. This means that the autocovariance is the same, no matter if defined by a time integral or by an expectation:</p>
<p>$$C_X(\tau)=\lim_{T\righ... | 542 |
spectral analysis | Spectrum Analysis using Windowed FFTs | https://dsp.stackexchange.com/questions/1357/spectrum-analysis-using-windowed-ffts | <p>I have a couple of questions regarding windowed FFTs:</p>
<ol>
<li><p>Why is the noise floor higher with windowed FFTs (according to Wikipedia's spectral leakage page, anyway), when the whole point of windowing is to reduce side lobes?</p></li>
<li><p>I realize that different windows are better for different things... | <p>A non-rectangular window will remove "noise" from distant bins at the cost of adding more "noise" to the immediately adjacent bins to a narrow-band spectrum peak. The sum of both these spectral leakage effects is greater than zero for a non-rectangular window. So if you count the raising of the level total of all a... | 543 |
spectral analysis | Difference of doing a PSD estimate of data and logarithmic transformed data? | https://dsp.stackexchange.com/questions/60931/difference-of-doing-a-psd-estimate-of-data-and-logarithmic-transformed-data | <p>What is the difference between doing a PSD estimate with data and the same data but which is logarithmically transformed before the estimate? Does it make the data more sinusoidal in nature?</p>
<p>An exercise in a book asks this question:</p>
<p>"For the lynx data, compare your spectral analysis results from the ... | <p>The exercise is instructive. Since this is an exercise, I will not do the full problem. I leave that to you.</p>
<p>grabbing the lynx data from</p>
<p><a href="https://www.encyclopediaofmath.org/index.php/Canadian_lynx_data" rel="nofollow noreferrer">https://www.encyclopediaofmath.org/index.php/Canadian_lynx_data... | 544 |
spectral analysis | Why look at power spectral density for stochastic processes? | https://dsp.stackexchange.com/questions/47740/why-look-at-power-spectral-density-for-stochastic-processes | <p>I have been told that for deterministic signals, it makes sense to look at their respective Fourier transforms/spectra. </p>
<p>For stochastic processes on the other hand, I am supposed to work with power spectral density in terms of qualitative analysis. </p>
<p>Why? </p>
| <p>Because a stochastic process itself doesn't <em>have</em> a Fourier transform.</p>
<p>That's really all there is to it.</p>
<p>You can only transform signals (i.e. functions over a body isomorphic to $\mathbb R$, for example, functions of time). You can't transform a random variable whose individual realizations a... | 545 |
spectral analysis | White gaussian noise analysis deduction | https://dsp.stackexchange.com/questions/71395/white-gaussian-noise-analysis-deduction | <p>I´m stuck in a deduction analysis of the variance of a gaussian white noise signal in a "integrate-and-dump detector" of a baseband data transmission receiver, where <span class="math-container">$n(t)$</span> is white noise with double-sided power spectral density <span class="math-container">$N_0/2$</span... | <p>They say that <span class="math-container">$n(t)$</span> is white noise with a double-sided power spectral density (PSD) of <span class="math-container">$N_0/2$</span>, i.e., the PSD is given by</p>
<p><span class="math-container">$$S_n(f)=\frac{N_0}{2}\tag{1}$$</span></p>
<p>The auto-correlation function is the inv... | 546 |
spectral analysis | Anyone know what algorithm the Spice AC Noise Analysis uses? | https://dsp.stackexchange.com/questions/42488/anyone-know-what-algorithm-the-spice-ac-noise-analysis-uses | <p>Anyone know what algorithm the Spice AC Noise Analysis uses?</p>
<p><a href="http://vision.lakeheadu.ca/eng4136/spice/noise_analysis.html" rel="nofollow noreferrer">http://vision.lakeheadu.ca/eng4136/spice/noise_analysis.html</a></p>
<p>Is it some spectral modeling synthesis? I.e. that it estimates the main signal... | <p>Noise analysis in Spice (Berkeley Spice) is done by summing up the power spectral density from every noise source in the circuit.
There are a couple caveats.</p>
<ol>
<li>The circuit is assumed to be linear.
In other words the circuit is first solved for a specific DC operating point then each of the components' e... | 547 |
spectral analysis | How to increase the spectral resolution? | https://dsp.stackexchange.com/questions/49291/how-to-increase-the-spectral-resolution | <p>My question is about the spectral resolution of a discrete signal. Each sample of my signal is made up with 2^n frames sampled at 44.1 kHz.</p>
<p>So, when I want to know the spectral resolution, I calculate : 44100/number_of_frames. With 2048 frames, my spectral resolution is around 20Hz. But, when I take a look t... | <p>You seem to have a good grasp of the tradeoffs. When using short-time Fourier analysis like you are, there is a version of the <a href="https://en.wikipedia.org/wiki/Uncertainty_principle" rel="nofollow noreferrer">uncertainty principle</a> at play. Increasing your time resolution (in your case, using a shorter DFT)... | 548 |
spectral analysis | FMCW radar signal processing: FFT with nonuniform sampling points | https://dsp.stackexchange.com/questions/96225/fmcw-radar-signal-processing-fft-with-nonuniform-sampling-points | <p>I have a behavioral model for a PLL that generates a chirp signal for an FMCW radar. To improve efficiency, the model outputs only the zero-crossing points at the negative edge.</p>
<p>From this zero-crossing data, I need to compute the RMS frequency error over a specific frequency range. However, since the sampling... | <p>Regardless of where your data comes from, if you have a non-uniformly sampled signal and wish to look at its spectral characteristics, there are a couple of ways to do it:</p>
<ul>
<li><p>Compute the non-uniform discrete Fourier transform directly (not very efficient): <span class="math-container">$X[f_k] = \sum_{n=... | 549 |
spectral analysis | Analyzing the quality of a music track | https://dsp.stackexchange.com/questions/48027/analyzing-the-quality-of-a-music-track | <p>I have a library of music tracks that I use to DJ with. Its currently about 3000 tracks that I have gather over the years. Some of it consists of low quality rips that I want to get rid of. </p>
<p>Currently I am writing a script that will look at the time/size = compression rate. Anything that is below 300kb/s I w... | <blockquote>
<p>Currently I am writing a script that will look at the time/size = compression rate. Anything that is below 300kb/s I want to delete.</p>
</blockquote>
<p>That's a very bad idea.</p>
<p>Just because something compresses well, because it fits the signal model of the compressor well, doesn't mean it's ... | 550 |
spectral analysis | Example of non-equivalence of the two PSD definitions | https://dsp.stackexchange.com/questions/55449/example-of-non-equivalence-of-the-two-psd-definitions | <p>According to the book <em>Introduction to Spectral Analysis</em> by P. Stoica and R. Moses, the power spectral density (PSD) <span class="math-container">$P(\omega)$</span> can either be defined as the discrete-time Fourier transform (DTFT) of the covariance sequence <span class="math-container">$r(k)$</span>, i.e.,... | <p><strong>Work in progress:</strong> wait till I am done before reading (and throwing brickbats!)</p>
<p>This question is difficult to answer without getting into a lot of details about basic signal analysis and Fourier transform theory.</p>
<p>Because of the way my brain works, I will discuss only real-valued <em>... | 551 |
spectral analysis | Good Continuing Education Course in the Basics of Frequency Analysis | https://dsp.stackexchange.com/questions/55853/good-continuing-education-course-in-the-basics-of-frequency-analysis | <p>All,</p>
<p>Are there any good continuing education courses of length 2-3 days to give an engineer a good background in Frequency Analysis. B&K used to teach one, but I don't think that they teach it anymore. I am looking for something that teaches sampling, aliasing, continuous vs. discrete signals, DFT, PSD... | 552 | |
spectral analysis | Units of a Fast Fourier Transform (FFT) and Spectrogram | https://dsp.stackexchange.com/questions/78188/units-of-a-fast-fourier-transform-fft-and-spectrogram | <p>What is the units of FFT, when doing Spectral Analysis of a Signal?</p>
<ol>
<li><p>For above question, the answer could be V or V/HZ for voltage signal. Which one is right? I would expect the result to be V.t or V/Hz because of dt.</p>
</li>
<li><p>I used <a href="https://www.mathworks.com/help/signal/ref/pspectrum... | <p>A few things to note here</p>
<ol>
<li>There are four different types of Fourier Transforms and they work all somewhat differently</li>
<li>The FFT is an implementation of the Discrete Fourier Transform (DFT), not the Continuous Fourier Transform FT. The DFT uses sums, the FT uses integrals</li>
<li>If your signal i... | 553 |
spectral analysis | Cross Power Spectral Density of Three Signals? | https://dsp.stackexchange.com/questions/94802/cross-power-spectral-density-of-three-signals | <p>I am performing a method of data analysis that requires estimating the CPSD between two measured signals. I actually have three signals, so I typically sum two of them and cross them with the third. Is there a analogous concept to the traditional cross power spectral density but for three signals at once? Or is ther... | <p>Didn't have the chance to write out an answer until now, but wanted to at least provide some mathematical explanation for your options.</p>
<p>Let's say you have signals <span class="math-container">$x_{1}(t),x_{2}(t),x_{3}(t)$</span>. What you are describing is computing the cross PSD between <span class="math-cont... | 554 |
spectral analysis | Cross Power Spectral Density of Unevenly Sampled Data | https://dsp.stackexchange.com/questions/8825/cross-power-spectral-density-of-unevenly-sampled-data | <p>Here's my problem. The input signals $x$ and $y$ will be having the time value aligned with each other. However, the data are not evenly sampled. I would like to calculate CPSD of both signals.</p>
<p>The solution comes to my mind is as follow</p>
<ol>
<li>$R_{xy}$ = cross correlation of $x$ and $y$ (I'm not sure ... | <p>One way would be to interpolate the signals to produce evenly-spaced samples and then calculate the CPSD as normal.</p>
| 555 |
spectral analysis | Analyze and reproduce sonic screwdriver sound | https://dsp.stackexchange.com/questions/58961/analyze-and-reproduce-sonic-screwdriver-sound | <p>Do you know about Doctor Who and its screwdriver?</p>
<p>Well, I'm trying to understand how to replicate <a href="https://web.archive.org/web/20060112064455/http://www.bbc.co.uk/doctorwho/sounds/sonicscrewdriver.mp3" rel="nofollow noreferrer">this sound</a> but the spectral analysis is too way complicated, just see... | <p><strong>An approximation</strong></p>
<p>Actually, the signal is not that complicated in my opinion. However, I am not a sounds guy... Just playing around with it a bit.</p>
<p>Interestingly, I have a very similar signal that I have produced (see attached sound file and spectrograms. Spectrogram above is my signal... | 556 |
spectral analysis | use wavelet for improving spectral resolution | https://dsp.stackexchange.com/questions/15587/use-wavelet-for-improving-spectral-resolution | <p>let us consider following code </p>
<pre><code>function [sca_1,sca_2,sca_3,sca_4]=calc_wavelet(y,wname,scales,freq,fs)
%y-input signal
%wname-wavelet basis name
%freq-test frequencies
%fs-sampling rate
TAB_Sca2Frq = scal2frq(scales,wname,1/fs);
[~,idxSca_1] = min(abs(TAB_Sca2Frq-freq(1)));
sca_1 = scales(idxSca_1)... | 557 | |
spectral analysis | Parameters for signal analysis | https://dsp.stackexchange.com/questions/16910/parameters-for-signal-analysis | <p>I am extremely new to signal analysis. And before posting I did a lot of reading on signal analysis, FFT and windowing. I am working on my thesis which involves comparison of speech signals lets say about 100 speech samples for a given sentence. I have the recordings and all the data. I have a few questions in order... | <p><strong>Noise removal</strong> </p>
<p>You should use a Gaussian convolution filter.</p>
<p><strong>Similarities in signal</strong></p>
<p>Generally this is done by spectrum analysis - like a Fourier transform. get the DTFT of say every second or half-second (you will need to experiment with window size to get be... | 558 |
spectral analysis | Estimating Average HR from PPG sensor | https://dsp.stackexchange.com/questions/75243/estimating-average-hr-from-ppg-sensor | <p>I am reading <a href="https://stm.sciencemag.org/content/10/431/eaap8674" rel="nofollow noreferrer">Smartphone based Blood Pressure Monitoring via the Oscillometric Finger Pressing Method</a>, which is trying to estimate blood pressure from a PPG sensor and a small applied force finger sensor. I am not an engineer, ... | 559 | |
spectral analysis | Find highest frequency of a very manky signal | https://dsp.stackexchange.com/questions/35028/find-highest-frequency-of-a-very-manky-signal | <p>I'm trying to compute the highest frequency (as can be sampled) in some pretty manky looking discrete time-dependent signals. My current method - a discrete fourier analysis - fails for some pretty awful looking but clearly oscillating signals (with discernable highest frequencies).</p>
<p>My current method is to c... | <p>I think most of your questions can be solved by subtracting then mean from the signal. Namely the all sinusoidal waves, with a nonzero frequency, have a mean of zero. So when the mean of a signal is not close to zero, then it will show up at 0 Hz (you can look at this as $\cos(0\,t)=1$).</p>
<p>After a closer look ... | 560 |
spectral analysis | Effect of DC component on the whole signal - comparison between normalised and non normalised | https://dsp.stackexchange.com/questions/34101/effect-of-dc-component-on-the-whole-signal-comparison-between-normalised-and-n | <p>I have a fourier analysis signal as in the picture attached, where red represents the FFT of movement of the hand of a stroke subject and the blue one is the movement of a healthy subject.</p>
<p>I am doing some analysis called <strong>Spectral Arc Length</strong>, where I will calculate the spectral arc length to ... | <p>As I understand from the description,you are not just using the DC information but also information at other frequencies.</p>
<p><strong>If this is the case:</strong> </p>
<p>Generally,Normalizing a signal means subtracting the mean value of the signal from the data.</p>
<pre><code>Y = Y - mean(Y) .......(1)
</co... | 561 |
spectral analysis | Spectral plot shows more notes than there really should be | https://dsp.stackexchange.com/questions/31151/spectral-plot-shows-more-notes-than-there-really-should-be | <p>I was experimenting with sound analysis lately and from what I see when I plot spectral data of an audio file is that apart from notes that were actually picked there are some other notes with quite high local amplitude.<br>
For example I have a sample where D major chord is played with some nasty distortion. After ... | <p>Since the notes from a guitar are no pure sinusoids, you should expect to see some harmonics, even when analyzing the dry signal without effects. E.g., the note E is the perfect fifth of the note A, i.e., it is the second harmonic.</p>
<p>If you use distortion or modulation effects (chorus, flanger, and phaser) you... | 562 |
spectral analysis | Deriving the impulse response of an ideal low-pass filter | https://dsp.stackexchange.com/questions/84934/deriving-the-impulse-response-of-an-ideal-low-pass-filter | <p>The impulse response of an ideal low-pass filter can be determined by setting <span class="math-container">$H(\omega)=1$</span> in the Fourier-representation <span class="math-container">$$h(n) = \frac{1}{2\pi}\int_{-\omega_c}^{\omega_c} H(\omega)e^{j\omega n}d\omega$$</span></p>
<p>The solution will be a function o... | <p>An additional gain (or attenuation) doesn't change the characteristic of a filter. So yes, any constant is fine. After all, it's matter of definition; there might be people who say that an ideal lowpass filter has unity gain. But that's quite a moot point in my opinion.</p>
<p>I do remember a case where a paper was ... | 563 |
spectral analysis | What kind of signal reppresents this Power Spectral Density? | https://dsp.stackexchange.com/questions/51538/what-kind-of-signal-reppresents-this-power-spectral-density | <p>I'm sampling 8 bioelectric signals with a embedded board which use an 8-channels ADC (<a href="http://www.analog.com/media/en/technical-documentation/data-sheets/AD7175-8.pdf" rel="nofollow noreferrer">AD7175-8</a>). My sampling rate for every single channel is about 6250 Hz. When move the analysis in the frequency ... | 564 | |
spectral analysis | Preparing audio data for FFT | https://dsp.stackexchange.com/questions/14546/preparing-audio-data-for-fft | <p>I would like to experiment with some input from a microphone and am receiving a 2 channel, 512 samples buffer in real time</p>
<p>I know the signal could be passed through a low pass filter, and then windowed before the FFT.</p>
<p>The sample rate is 44100.00, what low pass filter is needed for this, does the anal... | <blockquote>
<p>I know the signal could be passed through a low pass filter, and then windowed before the FFT.</p>
</blockquote>
<p>Yes, it <em>could</em> be, and it's usually advisable to use a window, but these are not just things you do blindly because you heard about them. Low passing the data will alter it in w... | 565 |
spectral analysis | How to interpret these different Fourier analysis of this audio signal? | https://dsp.stackexchange.com/questions/24635/how-to-interpret-these-different-fourier-analysis-of-this-audio-signal | <p>This is my first dive in DSP. I would like to familiarize myself with frequency analysis. I have two audio tracks which should be digitized at 16bit-44.1kHz and 24bit-192kHz (music, presented as a 24bit-192kHz sample) respectively.</p>
<p>I wanted to identify the effect of the low-pass filter around the Nyquist fre... | <p>If you look at the <a href="https://en.wikipedia.org/wiki/Window_function#Rectangular_window" rel="nofollow">Rectangular window</a> the best its rejection gets is about 40 dB. So that behavior, especially obvious in the bottom plot, for the rectangular window is to be expected.</p>
<p>I don't know for sure if this ... | 566 |
spectral analysis | What Fourier analysis would be appropriate for analyzing servo position error as a function of frequency? | https://dsp.stackexchange.com/questions/96070/what-fourier-analysis-would-be-appropriate-for-analyzing-servo-position-error-as | <p>I'm looking for a Fourier analysis method that will help me with a servo position tracking problem. I'll give some background:</p>
<p>Imagine I have a control system that attempts to control a linear actuator to a submicron position. I have a following error signal in units of nanometers that I monitor. In an ideal ... | <p>Possibly the reason this question has lain fallow is because it contains a factual error, and cannot be answered as stated.</p>
<blockquote>
<p>"For my 1000nm peak following error in the time domain, 800nm correspond to frequency range X, 100 nm frequency range Y, and the remaining 100nm correspond to the remai... | 567 |
spectral analysis | What is theorem under this formula? | https://dsp.stackexchange.com/questions/86160/what-is-theorem-under-this-formula | <p>I'm new to DSP. As I reading the textbook, I cannot understand the formula <span class="math-container">$X_{s}(f)=\frac{1}{T}\sum_{n=-\infty}^{\infty} X(f-nf_{s})$</span>. Could you please give me some keywords so I can learn the theorem and understand it?</p>
<blockquote>
<p>From spectral analysis, the original spe... | <p>It's not a <em>theorem</em>, but a <em>result</em> that is part of the <a href="https://en.m.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem" rel="nofollow noreferrer">sampling theorem</a>, and that shows the
<strong>sampling operation in the frequency domain:</strong></p>
<p>The sampling operation with ... | 568 |
spectral analysis | How to get fft bins of an audio signal to approach a BarkScale? | https://dsp.stackexchange.com/questions/96208/how-to-get-fft-bins-of-an-audio-signal-to-approach-a-barkscale | <p>I have an audio signal and I would like to do spectral analysis/processing on it.
I am interested in having frequency bins that approach a BarkScale rather than being equidistant.</p>
<p>First, I should mention that I am an amateur in DSP, please take it into account when answering.</p>
<p>I did some research and sa... | <p>No, that's not at all "frequency-warping to a Bark scale". That's just a frequency-domain equalizer (and a bad one, because you ignore the cyclic nature of the convolution theorem of the FFT; compare <a href="https://dsp.stackexchange.com/questions/6220/why-is-it-a-bad-idea-to-filter-by-zeroing-out-fft-bin... | 569 |
spectral analysis | Inconsistency between the units of power spectral density and the definition that people often give | https://dsp.stackexchange.com/questions/65963/inconsistency-between-the-units-of-power-spectral-density-and-the-definition-tha | <p>Perhaps someone can help me resolve something - this is my understanding:</p>
<p>In deterministic signal analysis, for a continuous signal <span class="math-container">$x(t)$</span> the <a href="https://en.wikipedia.org/wiki/Energy_(signal_processing)" rel="nofollow noreferrer">signal energy</a> is defined by
<span ... | <ul>
<li>The OP is correct in their dimensional analysis</li>
<li><span class="math-container">$|X(f)|^2$</span> is NOT the power spectral density, despite what other authors might claim. Other authors probably call this the power spectral density because it is close to right and it captures most of the important featu... | 570 |
spectral analysis | How to calculate time domain SNR using known sequence | https://dsp.stackexchange.com/questions/69380/how-to-calculate-time-domain-snr-using-known-sequence | <p>I am using the following formula to calculate SNR of a real world complex baseband signal sampled at 1x Nyquist.</p>
<pre><code>SNR = Rxy(tm)^2 / [ Px*Py - Rxy(tm)^2 ]
SNR (dB) = 10*log10(SNR)
</code></pre>
<p>where</p>
<pre><code>Rxy(tm) = peak of the cross correlation at time delay, tm
Px = power in referenc... | <p>The peak of the cross correlation should be the transmit signal power times the channel's attenuation.</p>
<p>Realizing that, it's really just</p>
<p><span class="math-container">\begin{align}
\text{SNR} &= \frac{P_\text{signal}}{P_\text{noise}}\\
&= \frac{P_\text{signal}}{P_\text{received} - P_\text{signal}... | 571 |
spectral analysis | Purpose of using polyphase filter bank (PFB) | https://dsp.stackexchange.com/questions/24166/purpose-of-using-polyphase-filter-bank-pfb | <p>What is the advantage of using a polyphase filter bank (PFB) for spectral analysis over just using the FFT? In the standard <a href="http://cnx.org/contents/3dea9cf9-32b6-4bf2-940b-cf8d251a0a84@15/Uniformally_Modulated_%28DFT%29_Fi" rel="nofollow">"critically sampled" uniform DFT filterbank</a>, the polyphase decima... | <p>One advantage of a polyphase filterbank approach is, as you guessed, that you can control the frequency response of each channel. When using a DFT alone, you have limited control over the frequency band covered by each bin (characterized by a <a href="https://en.wikipedia.org/wiki/Dirichlet_kernel" rel="nofollow">Di... | 572 |
spectral analysis | Filter length in maximally decimated polyphase channelizer | https://dsp.stackexchange.com/questions/91992/filter-length-in-maximally-decimated-polyphase-channelizer | <p>I would like to know whether there is a condition in selecting the number of channels <span class="math-container">$M$</span> and filter length <span class="math-container">$N$</span>. As of now I am trying to design a channelizer where the data length <span class="math-container">$M$</span> is much less than the FI... | <blockquote>
<p>The paper provides a solution to the problem by stacking the filter coefficients such that the the number of taps per channel will increase (where filter length N=M⋅K and finally the number of filter taps per channel is K).</p>
</blockquote>
<p>That's not specific to the paper, that's just how polyphase... | 573 |
spectral analysis | Detect repetitive units within signals | https://dsp.stackexchange.com/questions/22306/detect-repetitive-units-within-signals | <p>I have several signals that consist of repetitive units. In the figure you'll clearly see the variability of the signals, that increases top down. The first signal is super repetitive and units are indicated with green lines.
In the third, you'll see peaks and in the middle a little insertion that I know consists of... | <p>Your repetitive signal seem to be in a lower rate than the noise. I would run an FFT (why short) on all 6 sequences and filter out (zero) the frequencies that are clearly attributed to noise and then run an inverse FFT.
If you know the repetition rate you might select the one frequency that has the correct informat... | 574 |
spectral analysis | How to eliminate a cyclic spectrum estimation window artifact? | https://dsp.stackexchange.com/questions/83096/how-to-eliminate-a-cyclic-spectrum-estimation-window-artifact | <p>I am using an implementation of the averaged cyclic periodogram (section 3.2.4 in Antoni, Jérôme. "Cyclic spectral analysis in practice." Mechanical Systems and Signal Processing 21.2 (2007): 597-630.). The cyclic spectrum is estimated based on two <span class="math-container">$L$</span> ln
<span class="ma... | <p>Answer found in a Boustany, Roger, and Jérôme Antoni. "Cyclic spectral analysis from the averaged cyclic periodogram." IFAC Proceedings Volumes 38.1 (2005): 166-171.</p>
<p>The article states that the artifact is due to leakage and it is solved by increasing the overlap between the CSD windows. Sensitivity... | 575 |
spectral analysis | How to convert SPL [dB] in PSD [Watt/Hz]? | https://dsp.stackexchange.com/questions/96486/how-to-convert-spl-db-in-psd-watt-hz | <p>I want to calculate vibro-acoustic analysis of plate in program Ansys workbench Mechanical.</p>
<p>Tell me please how to convert Sound Pressure Level [dB] in Power Spectral Density [Watt/Hz] ?</p>
| <p>Tricky.</p>
<p>Assuming a level of <span class="math-container">$L_{SPL}$</span> in dB and that your application uses the standard sound pressure reference of <span class="math-container">$p_{ref} = 20\mu Pa$</span> we can calculate the RMS sound pressure as</p>
<p><span class="math-container">$$p = p_{ref} \cdot 10... | 576 |
spectral analysis | Forecasting with ARMA models, from a filter point of view | https://dsp.stackexchange.com/questions/23606/forecasting-with-arma-models-from-a-filter-point-of-view | <p><a href="https://en.wikipedia.org/wiki/Autoregressive_integrated_moving_average" rel="nofollow">ARMA</a>
models are afaik just filters with transfer function
$ {MA(z) \over AR(z)} \equiv {FIR(z) \over IIR(z)} $ .<br>
However forecasters of stock prices, market trends ...<br>
seem to be mainly statisticians, with t... | <p>ARMA divides the signal into two parts and that models the two parts. </p>
<p>Financial time series are corrupted by different types of correlated and uncorrelated noises with definite functions that allow modeling and others more difficult as per having to use aproximations. In addition financial or economic time... | 577 |
spectral analysis | Extraction of non-sinusiodal repetition rates | https://dsp.stackexchange.com/questions/2119/extraction-of-non-sinusiodal-repetition-rates | <p>I have an auto-correlation function that was generated from a signal, and I am trying to extract its 'repetition rate' in order to calculate the dominant frequency of the pulse, but I am not exactly clear how to do this. </p>
<p>Here are two cases, labelled 'good' and 'bad' to mark best/worst case scenarios. What m... | <blockquote>
<p>You are right that the repetition is around 650 by how exactly do I compute that automatically? Seems like a peak-picking problem to me? Or is there some other methods that can be used?</p>
</blockquote>
<p>Yes, it's just peak-picking. Your period is the x value of the first strong peak:</p>
<p><im... | 578 |
spectral analysis | Paper replication: Validating the proper way to pass .wav audio breathing data through a bandpass filter | https://dsp.stackexchange.com/questions/76605/paper-replication-validating-the-proper-way-to-pass-wav-audio-breathing-data-t | <p>I am working on trying to apply a low and high pass filter to an audio file that contains a set of exhalations over a microphone. The inhalations have been cut out of the file, and the exhalations are stitched together in the file. I am attempting to replicate this <a href="https://jamanetwork.com/journals/jamaotola... | <p>From the paper</p>
<blockquote>
<p>we used a microphone that has a low-pass filtered with a cutoff frequency at 10 Hz and a high-pass filtered at 150 Hz and is amplified by 20 dB</p>
</blockquote>
<p>This makes no sense whatsoever. If you lowpass filter audio at 10 Hz, you have nothing left. I'm guessing it's a typo... | 579 |
spectral analysis | Kullback-Leibler Distance of Spectral Data | https://dsp.stackexchange.com/questions/37279/kullback-leibler-distance-of-spectral-data | <p>I am currently reading through <a href="https://www.cs.cmu.edu/~rbd/papers/dannenberg-goto-structure-2009.pdf" rel="nofollow noreferrer">Music Structure and Analysis from Acoustic Signals</a> and am having some difficulty in understanding how the modified Kullback-Leibler distance is calculated. (I am just very rec... | <p>The expression in your question seems to have been written for univariate Gaussians. For multivariate Gaussians,
$KL(A,B) = \frac{1}{2}\left[\log\frac{|\Sigma_B|}{|\Sigma_A|} - d + Tr(\Sigma_B^{-1}\Sigma_A) + (\mu_B - \mu_A)^T \Sigma_B^{-1}(\mu_B - \mu_A)\right]$
where $d$ is the dimensionality of the feature vecto... | 580 |
spectral analysis | Why is it used the Power Density Spectrum (PSD) over an anylisis with the Fast Fourier Transform (FFT)? | https://dsp.stackexchange.com/questions/70103/why-is-it-used-the-power-density-spectrum-psd-over-an-anylisis-with-the-fast-f | <p>I'm currently working with physiological signals (PPG and GSR) for emotion recognition but, from my research, I've found out that almost everyone in that area use a PSD analysis over a FFT analysis. I've been reading about them and found out that PSD helps with giving a clearer view of the spectrum despite the amoun... | 581 | |
spectral analysis | FFT of signal data with windowing, overlapping and averaging | https://dsp.stackexchange.com/questions/85303/fft-of-signal-data-with-windowing-overlapping-and-averaging | <p>This is my first ever question here so the help is really appreciated.</p>
<p>I am performing FFT on a signal. I want to perform windowing, 50% overlapping and averaging to the signal. There is a function <code>scipy.signal.welch</code> to perform this automatically but the output is in power spectral density. I wan... | <blockquote>
<p>I want to perform windowing, 50% overlapping and averaging to the signal</p>
</blockquote>
<p>This makes sense for magnitude, but not for phase.</p>
<blockquote>
<p>Is there a way to compute phase shift from power spectral density</p>
</blockquote>
<p>No. The PSD is computed by averaging magnitude spect... | 582 |
spectral analysis | Basic questions about spectral leakage | https://dsp.stackexchange.com/questions/96427/basic-questions-about-spectral-leakage | <p>Let <span class="math-container">$x(t)$</span> be a periodic signal with period <span class="math-container">$T>0$</span>. Suppose we sample <span class="math-container">$x(t)$</span> with sample rate <span class="math-container">$f_s\in\mathbb N$</span> in the interval <span class="math-container">$[0,T)$</span>... | 583 | |
spectral analysis | Adding noise to an ECG signal | https://dsp.stackexchange.com/questions/6103/adding-noise-to-an-ecg-signal | <p>I am doing a project on ECG arrythmia analysis using matlab.</p>
<ol>
<li><p>I have designed notch filter for removing 50 Hz noise but don't know how to add a 50 Hz powerline interference noise to a clean ECG signal? </p></li>
<li><p>Also, I want to check whether noise is reduced in the filtered signal. Will Power ... | <p>1) Create a 50 Hz sinusoid and then simply add it to your ECG signal. You can control the power of the 50 Hz noise by multiplying the sinusoid by some gain factor (can be less than or more than 1) before you add it to the ECG.</p>
<p>2) I'm not familiar with the Welch periodogram, but if it displays the power spec... | 584 |
spectral analysis | Why Cramér spectral representation and not DTFT for stochastic process | https://dsp.stackexchange.com/questions/68936/why-cram%c3%a9r-spectral-representation-and-not-dtft-for-stochastic-process | <p>In a lot of time-series analysis references I find (written by mathematicians or statisticians rather than engineers), I find the following signal decomposition for a stochastic process, termed the "Cramér representation" (e.g. eqn 8.11 of this <a href="https://www.stat.tamu.edu/%7Esuhasini/teaching673/cha... | <p>I will introduce some terminology and intuition that will be helpful when reading other references. It will be neither complete nor completely rigorous.</p>
<hr>
The measures that we first encounter in real analysis assign <i>sizes</i> (non-negative real numbers) to <i>measurable</i> subsets of <span class="math-con... | 585 |
spectral analysis | When do phases not exist for spectrograms? | https://dsp.stackexchange.com/questions/58680/when-do-phases-not-exist-for-spectrograms | <p>I have been reading a paper on the <a href="https://ieeexplore.ieee.org/document/7251907" rel="nofollow noreferrer">"Single pass spectrogram inversion"</a> </p>
<p>and I came across this in the Introduction part.</p>
<blockquote>
<p>In many applications, the analysis and modification of the Short-Time
Fourier ... | 586 | |
spectral analysis | Analysing DAC Spectra: Transient Noise Analysis | https://dsp.stackexchange.com/questions/73872/analysing-dac-spectra-transient-noise-analysis | <p>I am working with a new Digital-to-Analog Converter (DAC) design in simulation and I'm trying to analyse the output. The device takes in an ideal 14-bit digital representation of a sine wave and outputs through an ideal Butterworth filter (a̶n̶t̶i̶-̶a̶l̶i̶a̶s̶i̶n̶g̶ anti-imaging).</p>
<p>In the simple analyses, I h... | 587 | |
spectral analysis | Complex Spectral Phase Evolution (CSPE) Performance depending on signal windowing? | https://dsp.stackexchange.com/questions/57905/complex-spectral-phase-evolution-cspe-performance-depending-on-signal-windowin | <p>I am look into CSPE. "<a href="http://jssunderlin.pbworks.com/f/13449.pdf" rel="nofollow noreferrer">Signal Analysis Using the Complex Spectral Phase Evolution (CSPE) Method</a>"</p>
<p>The method is simple. It compares the original signal's FFT and shifted signal FFT in phase domain so that it can get an estimate ... | 588 | |
spectral analysis | Auto-correlation of time signals | https://dsp.stackexchange.com/questions/43529/auto-correlation-of-time-signals | <p>I'm interested in papers which are about auto-correlations of periodic <strong>time series</strong> signals.All relevant papers and applications are interesting to me, as I am studying the properties of the auto-correlation of periodic, digital time signals.</p>
<p>The reason, I am asking you for this help,is that ... | 589 | |
spectral analysis | Issues with ML Pattern Recognition After Bandpass Filtering | https://dsp.stackexchange.com/questions/88988/issues-with-ml-pattern-recognition-after-bandpass-filtering | <p>We've been working on a machine learning project for pattern recognition, using time-domain features such as kurtosis, mean, standard deviation, variance, skewness, and peak-to-peak values.</p>
<p>Background:</p>
<p>Initially, we trained our data after applying a high-pass filter at 1 kHz. The results were satisfact... | 590 | |
spectral analysis | Finding the best principle component | https://dsp.stackexchange.com/questions/16432/finding-the-best-principle-component | <p>The title might be unclear, but the problem is this. I have a signal sampled 1500 times with a rate of 60/s, and a sensor array 512 units large. There is a lot of noise, echo and other frequencies being picked up, but I am interested in only one. First I do a spike removal, then a bandpassfilter (butterworth) around... | <p>By doing PCA, the principal components you will get will not correspond to a single recording, but rather to a mix between them. PCA is a feature extraction method, whereas what you are looking for, seems to me, as a feature selection problem.</p>
<p>Also, if you have so many simultaneous recordings, all affected b... | 591 |
spectral analysis | the demonstration that states that the FT of the ACF function is the square of the DTFT of the signal | https://dsp.stackexchange.com/questions/59380/the-demonstration-that-states-that-the-ft-of-the-acf-function-is-the-square-of-t | <p>I am following the book The Intuitive Guide to Fourier Analysis & Spectral Estimation with MATLAB. I am trying to selflearn the fourier analysis in matlab.
I got lost in one passage in the demonstration that states that the FT of the ACF function is the square of the DTFT of the signal. I have attached it here<a... | <p>You are right, the derivation is full of typos. The first equation below Eq. <span class="math-container">$(8.39)$</span> should read</p>
<p><span class="math-container">$$\int_{-\infty}^{\infty}x(t+\tau)e^{\color{red}{-}j\omega\tau}d\tau=X(\omega)e^{j\omega \color{red}{t}}\tag{1}$$</span></p>
<p>Substituting into... | 592 |
spectral analysis | Strong vs weak COLA (constant overlap-add) | https://dsp.stackexchange.com/questions/81687/strong-vs-weak-cola-constant-overlap-add | <p>My question is on the aliasing cancellation of the OLA method when spectral modification is involved. The book related to this question is given by <a href="https://ccrma.stanford.edu/%7Ejos/sasp/Constant_Overlap_Add_COLA_Cases.html" rel="nofollow noreferrer">this link</a>.</p>
<p>As stated by the webpage, for weak ... | 593 | |
spectral analysis | $i^{\text{th}}$-dimensional autocorrelation function | https://dsp.stackexchange.com/questions/91730/i-textth-dimensional-autocorrelation-function | <p>I am referring to the work of Stephen A. Billings on "<a href="https://eprints.whiterose.ac.uk/87212/1/acse%20research%20report%2056.pdf" rel="nofollow noreferrer">Identification of a class of nonlinear systems using correlation analysis</a>" from the year 1978, where it is mentioned that the <span class="... | <p>The statement is provably true:</p>
<ol>
<li><span class="math-container">$x(t)$</span> is zero mean and Gaussian with variance 1.</li>
<li><span class="math-container">$$E[x(t_i)x(t_j)] = \begin{cases} 0 \mbox{ for } t_i \not= t_j \\
1 \mbox{ for } t_i = t_j\end{cases}$$</span></li>
</ol>
<p>For <span class="math-c... | 594 |
spectral analysis | Questions on Cepstral Analysis | https://dsp.stackexchange.com/questions/89115/questions-on-cepstral-analysis | <p>I have a few questions regarding cepstral analysis, that the numerous articles and papers I've read on the topic didn't answer.</p>
<p><strong>What I understood:</strong> The cepstrum captures the periodicity of harmonics in a spectrum.</p>
<p><strong>My questions:</strong>
In articles treating about default detecti... | <p>A cepstrum not only captures the periodicity of harmonics within a spectrum, but also the much wider envelope covering the total width of the harmonics across the spectrum (consider that to be a window on an infinite harmonic train.) The envelope is usually represented by a much lower set of quefrencies in the cepst... | 595 |
spectral analysis | Feature extraction for sound recognition and classification | https://dsp.stackexchange.com/questions/21961/feature-extraction-for-sound-recognition-and-classification | <p>I am building an application that would "listen" to the microphone input, analyse it, and compare the analysis to a pre-analysed and pre-classified sound bank (small - maximum 20 sounds). It will then show the user what sound it was.</p>
<p>Now, I have a vague idea on how to implement this. I would like to choose a... | <p>Have a look @ <a href="https://github.com/bmcfee/librosa/" rel="nofollow noreferrer">librosa</a>, a simple python library for audio analysis, implementing common features. Here is a <a href="https://github.com/librosa/librosa/blob/main/examples/LibROSA%20demo.ipynb" rel="nofollow noreferrer">great introduction and ... | 596 |
spectral analysis | Help with denoising signal and periodogram analysis resources | https://dsp.stackexchange.com/questions/71917/help-with-denoising-signal-and-periodogram-analysis-resources | <p>This is a cross posting from the crossvalidated stack exchange as I thought this may be a better forum to ask.</p>
<p>I have a dataset consisting of respiratory time series signals of different lengths obtained from different groups of patients. I want to either classify or cluster the patients using these timeserie... | <blockquote>
<p>Firstly, I am confused if I am supposed to filter my signals to get rid of any frequencies above the Nyquist frequency. My sampling frequency is 32Hz and my time series is somewhat noisy and has some artifacts. I am also unsure of which filter to select for this.</p>
</blockquote>
<p>That ship has saile... | 597 |
spectral analysis | Right algorithm for fourier transform on physical heights | https://dsp.stackexchange.com/questions/10207/right-algorithm-for-fourier-transform-on-physical-heights | <p>I have data from a LIDAR unit that I would like to get the spectral density of. Unfortunately, the only thing I remember from my Fourier analysis class are the methods that I know will not work.</p>
<p>The data comes from a 1D LIDAR scan of a (mostly flat) surface, which returns radial distance at evenly spaced $d\... | <p>Your question seems to have a couple of nested issues: First off, the computation of the Power-Spectral-Density is as straight forward as the computation of the signals' <a href="http://en.wikipedia.org/wiki/Discrete_Fourier_transform" rel="nofollow">Discrete Fourier Transform</a>, (DFT), followed by its absolute ma... | 598 |
spectral analysis | Detecting a frequency swept sinusoid and its parameters? | https://dsp.stackexchange.com/questions/18950/detecting-a-frequency-swept-sinusoid-and-its-parameters | <p>Given a (FFT-sized) frame of data, and detection of a spectral component statistically above the noise floor in the FFT of this window, what characteristics or signal analysis could be used to determine that this spectral component is more likely to be a linearly swept sinusoid, rather than one that is stationary ac... | <p>You could compute the instantaneous frequency of the signal in the frame. This can be done as outlined in <a href="https://library.seg.org/doi/abs/10.1190/1.1443220?journalCode=gpysa7" rel="nofollow noreferrer">this paper</a> (e.g. Eq.(9)). You need to compute the analytic signal using a Hilbert transformer:</p>
<p... | 599 |
filtering | Can I use BRISQUE to compare different filtering techniques for the same acquired image? | https://dsp.stackexchange.com/questions/71033/can-i-use-brisque-to-compare-different-filtering-techniques-for-the-same-acquire | <p>BRISQUE compares your image with a pre-learned model with opinion scores. I am not sure about this but would image resolution affect the result of BRISQUE?</p>
<p>Moreover, if I have 2 filters and I would like to compare the results of using either filter to get the better result, can I use BRISQUE to quantify the b... | 600 | |
filtering | LPF - signal values unaffected at specific times | https://dsp.stackexchange.com/questions/21774/lpf-signal-values-unaffected-at-specific-times | <p>Is it possible to design an LPF that has an output identical to the input at specific points in time domain (the rest of the input waveform can get filtered/distorted)?
Is there a general name/technique for this kind of thing (assuming it is possible), so that I can search for more information on this topic?</p>
| <p>What you probably are looking for are Nyquist/$M$th-band filters. The impulse response of these have the following property (assuming a non-causal impulse response centered around tap 0 for ease of exposition)</p>
<p>$h_n = \left\{ \begin{matrix} \frac{1}{M} & n=0\\ 0 & n = kM, k=\pm 1, \pm 2, \dots\end{mat... | 601 |
filtering | Shock filtering using structure tensor | https://dsp.stackexchange.com/questions/32409/shock-filtering-using-structure-tensor | <p>my name is niladri, I am new to image processing(actually this is my first code). I want to implement shock filter using structure tensor. I have rough idea of what structure tensor is and implemented in MATLAB. But to design a shock I need to calculate the sign using the dominating eigenvector. But as for my unders... | <p>I think that the question here is "how is the dominant direction of the local slope actually estimated?" with the outlook of using it in a shock filter.</p>
<p><a href="http://www.eurasip.org/Proceedings/Eusipco/Eusipco2012/Conference/papers/1569582949.pdf" rel="nofollow">A Shock Filter is applied iteratively</a> a... | 602 |
filtering | How is Bayesian Estimation related to filtering? | https://dsp.stackexchange.com/questions/35526/how-is-bayesian-estimation-related-to-filtering | <p>I am reading about <a href="http://rads.stackoverflow.com/amzn/click/0133457117" rel="nofollow noreferrer">estimation theory</a>, including topics like Bayesian Estimation (e.g. Wiener Filtering).</p>
<p>It seems that we usually define a filter in terms of tis frequency response (e.g. High Pass, Low Pass). On the o... | <p>In Wiener filtering, you filter a noisy signal to more closely resemble a <em>desired</em> signal that you have access to. In Bayesian estimation, you take <em>prior knowledge</em> into account to estimate some state given noisy measurements. In frequency filtering, you just remove frequency content from a signal.... | 603 |
filtering | How to filter key clicks? | https://dsp.stackexchange.com/questions/36589/how-to-filter-key-clicks | <p>I am the author of an amateur radio application that produces a waterfall display across a range of frequencies. Time is on the $x$-axis, frequency is on the $y$-axis, and the relative strength of each signal is depicted by the intensity of color.</p>
<p>Some of the signals have, what are called, <em>"key clicks"</... | <p>Assuming from your screenshot that the frequency magnitudes of "key clicks" are always higher (brighter) than the normal signal, you could just employ a basic <a href="https://en.wikipedia.org/wiki/Limiter" rel="nofollow noreferrer">Limiter</a>? In other words, if a frequency magnitude value exceeds a certain thresh... | 604 |
filtering | How can i create a low pass filter in matlab | https://dsp.stackexchange.com/questions/41619/how-can-i-create-a-low-pass-filter-in-matlab | <p>i am trying to create a low pass filter in matlab for a project in signals and systems class but i couldn't. cut off frequency is 500 , sampling frequency is 10000 and the low pass filter's band width is 150 Hz. If you help me i would be very appreciated</p>
| <p>filterDesigner Filter Designer
filterDesigner launches the Filter Designer.
Filter Designer is a Graphical User Interface (GUI) that allows you to
design or import, and analyze digital FIR and IIR filters.</p>
<pre><code>If the DSP System Toolbox is installed, Filter Designer seamlessly
integrates advan... | 605 |
filtering | Recommendation for studying filters | https://dsp.stackexchange.com/questions/45193/recommendation-for-studying-filters | <p>I have a project to do about what happens to a periodic function when we pass it through a low-pass, high-pass and band-pass filter.
I have no expressions for the filters or the function, I just have to analyse graphics.
I already concluded that the low-pass filter passes the zones of the graphic that have a low v... | <p>If you have some numerical methods background, Richard Hammings, Digital Filters, is a good place to start. The book is from 1977 but the math hasn’t changed. The book has also been released by Dover so it has a very low price, unlike Oppenheim and Schaefer’s book and also unlike Oppenheim and Schaefer, is compa... | 606 |
filtering | filter multiple sources from each other | https://dsp.stackexchange.com/questions/53871/filter-multiple-sources-from-each-other | <p>I am trying to supply a solution for recording a court room and then, use some smart algorithms in order to automatically convert the speech to text.</p>
<p>In order to do that I have three boom microphones, one is near the judge, the second is on A side and the third one on the B side. this way i get 3 different s... | <p>That's called <em>source separation</em>, and higher-end conference table systems already do that<sup>citation needed</sup>.</p>
<p>You'll be able to find quite a bit of literature if you search for that term, but an easy approach would be to assume that things are linear (sadly, in audio, that's not really often t... | 607 |
filtering | Can filter "depth" be adjusted by mixing dry and wet signals? | https://dsp.stackexchange.com/questions/24831/can-filter-depth-be-adjusted-by-mixing-dry-and-wet-signals | <p>Can filter "depth" be adjusted by mixing dry and wet signals? </p>
<p>I.e. can I simulate e.g. a +6dB bandshelf/peak filter at 1kHz by mixing in some of the dry unequalized signal and some of a wet signal that has been bandpass filtered at 1kHz and the filter has around the same shape as the bandshelf/peak. </p>
<... | <p>adding the input to the output of a scaled 2nd-order bandpass IIR <strong>will</strong> get you the classic peak/cut EQ curve.</p>
<p>adding the input to the output of a scaled 1st-order LPF or HPF <strong>will</strong> get you a 1st-order low-shelf or high-shelf EQ.</p>
<p>adding the input to the output of a scaled... | 608 |
filtering | How to design a phonographic sound filter in python? | https://dsp.stackexchange.com/questions/84182/how-to-design-a-phonographic-sound-filter-in-python | <p>I'm making a phonographic filter or simulator to make one of my songs to sound as if it was recorded on a phonographic cylinder.</p>
<p>Two important things about phonographic recoding is that sound gets more treble when it's louder and also that the recording of the wave is made top to bottom so the negative part o... | 609 | |
filtering | Adding channel effects to a signal | https://dsp.stackexchange.com/questions/25501/adding-channel-effects-to-a-signal | <p>I have a a channel matrix "H" that is circulant.
I have data blocks.
I want to add the channel effects to the signal. </p>
<p>When H was only a vector of channel coefficients I would say:</p>
<pre><code>%Going Through The Channel
After_channel= filter(H,1,Data);
</code></pre>
<p>but now that H is a matrix the l... | <p>This is a small example of how to implement this in Matlab:</p>
<pre><code>h=[0.4070; 0.8150; 0.4070]; % Channel: Proakis A
d=[1; -1; 1; 1]; % Data
H=convmtx(h,4); % Channel Matrix
y1=H*d; % Matrix approach
y2=conv(h,d); % Convolution
y1-y2
</code></pre>
| 610 |
filtering | An intuitive explanation as to why a matched filter is time reversed? | https://dsp.stackexchange.com/questions/70173/an-intuitive-explanation-as-to-why-a-matched-filter-is-time-reversed | <p>It easy enough to study correlation, and matched filters. But the challenge I see unmet anywhere to date and which I struggle to meet myself is a simpler presentation, to with more difficult task I suspect.</p>
<p>Can you explain, in lay terms, to satisfy the intuitions of a listener, why the matched filter is a tim... | <p>Picture the transmitted signal as a «signature». You want to find some process that maximize the probability of detecting that signature even when there is noise.</p>
<p>What do you do to find some signature buried in noise? You make a template that exactly match the known signature, and you slide it back or forth i... | 611 |
filtering | The result if order of two filter are reversed | https://dsp.stackexchange.com/questions/73111/the-result-if-order-of-two-filter-are-reversed | <ol>
<li>Apply the Composite Laplacian Filter first, then apply the gaussian filter.</li>
<li>Apply the gaussian filter first, then apply the composite laplacian filter.</li>
</ol>
<p>My work as below:
Here we assume the original image is function <span class="math-container">$f(x,y)$</span>
<span class="math-container... | <p>Formally, (linear) derivatives and convolutions may commute, as explained on <a href="https://en.wikipedia.org/wiki/Convolution#Differentiation" rel="nofollow noreferrer">Wikipedia-Convolution/Properties/Differentiation</a>. This is a major "operation-saving" property: if one wants to differentiate many im... | 612 |
filtering | Does a filter add oscillations to a signal? | https://dsp.stackexchange.com/questions/38171/does-a-filter-add-oscillations-to-a-signal | <p>this is a more general version of a <a href="https://dsp.stackexchange.com/q/38108/4298">question which i asked previously</a>.</p>
<p>From what I understand, the purpose of a filter is to change the amplitude of a specific frequency band.</p>
<p>As I went through the analytic calculation of a filtered (2nd order)... | <p>There are two unrelated phenomena that need to be understood in this context. First of all, as pointed out in the answers by <a href="https://dsp.stackexchange.com/a/38177/4298">hotpaw2</a> and by <a href="https://dsp.stackexchange.com/a/38172/4298">MBaz</a>, an LTI system cannot add any frequency components to an i... | 613 |
filtering | Remove high resolution spurious peaks from sinusoidal signal | https://dsp.stackexchange.com/questions/46281/remove-high-resolution-spurious-peaks-from-sinusoidal-signal | <p>I have the current from a LEM transducer measured. The measurement is taken on the output of a transformer. The signal is a 50 Hz signal, measured at 100kHz. When the demand of the system is increased the current increases and therefore the amplitude of the sinusoidal gets bigger. I am looking for the maximum curren... | <p>Since the spikes are regions of bad data you want to figure out how to identify where they are and exclude them from your analysis. You certainly have more than enough sampling points to get a good read on the signal parameters on the regions that are good.</p>
<p>You indicate that you are looking for the amplitud... | 614 |
filtering | Filtering Overlapping Frequencies in sound file | https://dsp.stackexchange.com/questions/19485/filtering-overlapping-frequencies-in-sound-file | <p>I have been given a sound file of a plane passing over a rain forest filled with birds. I am supposed to filter out the sound of the plane as it flies over. I've accomplished this with various types of filters in MATLAB, but I always run into one problem. I can either cut out all of the plane and lose some of the b... | <p>In my opinion, the best approach for this kind of spectrally-overlapping noise is to use blind source separation techniques, like independent component analysis (ICA) or time-frequency masking, or sparse source decomposition. Look up the work of Emmanuel Vincent, Kostas Kokkinakis, or Philipos Loizou. These method... | 615 |
filtering | Filtering out a specific frequency in an analog signal | https://dsp.stackexchange.com/questions/24782/filtering-out-a-specific-frequency-in-an-analog-signal | <p>I'm wondering how I would go about filtering out a regular sine-wave signal with a constant frequency and voltage.</p>
<p>I'm really new to the whole DSP-area but imagine I would have a regular sinewave at a specific frequency (let's say 30Hz), and on top of that signal I have a bunch of other small peaks (which ar... | <p>A notch filter is a good approach in general for removing an unwanted frequency. But if you are certain of the <strong>exact</strong> frequency, phase and amplitude of the unwanted sine wave, then you may also consider adding the noisy signal to a sine wave of the same frequency and amplitude but 180 degrees out of ... | 616 |
filtering | Use of an impulse-response system to model sediment transport along a river reach | https://dsp.stackexchange.com/questions/46302/use-of-an-impulse-response-system-to-model-sediment-transport-along-a-river-reac | <p>I am new to signal processing and have come into the subject from the study of rivers and basic geophysics. I am trying to test an idea previously put forward that the sediment transport response of rivers can be modeled as a linear impulse-response system. Transport along a river reach changes as the upstream suppl... | 617 | |
filtering | How the zero - phase filter without filtered signal truncation at the end can be implemented? | https://dsp.stackexchange.com/questions/55372/how-the-zero-phase-filter-without-filtered-signal-truncation-at-the-end-can-be | <p>I mean what for the window FIR filter the filtered signal is truncated at the end because impulse response of the filter is symmetric. For example the code from here <a href="https://github.com/tmk/tmk_keyboard/blob/master/tmk_core/tool/mbed/mbed-sdk/workspace_tools/dev/dsp_fir.py" rel="nofollow noreferrer">(in pyth... | <p>You can either gather more data at the end than you need for output, or zero pad past the end of your data with at least half the length of your zero-phase filter. </p>
<p>If you can’t get data past the “ends”, and don’t like the artifacts from zero-padding, then you might try other reasonable assumptions (circula... | 618 |
filtering | Accelerometer drift: What hardware-level signal conditioning operations are being performed under the hood of a MEMS accelerometer chip? | https://dsp.stackexchange.com/questions/72732/accelerometer-drift-what-hardware-level-signal-conditioning-operations-are-bein | <p>I'm in a debate with a peer who says that filtering accelerometer signals at the chip-level has nothing to do with mitigating the problem of drift</p>
<p>Often, additional software-level filtering is employed to smooth noise, depending on the application. But My question pertains to any filtering or processing that ... | 619 | |
filtering | Strange noises when filtering audio signal | https://dsp.stackexchange.com/questions/8272/strange-noises-when-filtering-audio-signal | <p>I am using Naudio open source library and I am trying to do some simple filtering. The problem is that I hear some "clicks", not too loud. The library offers me the possibility to use at least two buffers, so the computing time doesn't introduce a delay between them. Because in the most of the time I am dealing wit... | <p>The context in which you use these functions is not clear, but it seems to me that your problem is "edge effects".</p>
<p>When you are evaluating the convolution or the biquad, you need to access samples which are outside the current buffer. Your two implementations evaluate these samples as zero. This is incorrect... | 620 |
filtering | Blurring transfer function of image | https://dsp.stackexchange.com/questions/16457/blurring-transfer-function-of-image | <p>I need help solving the following blurring function question.Assume an image $f(x,y)$ is moving in front of a camera so that $𝑥_0(𝑡)$ and $𝑦_0(𝑡)$ are the time-varying components of motion in the x- and y- directions respectively. The camera’s shutter opens at 𝑡 = 0 and closes at 𝑡 = 𝑇. Assume that the shutte... | <p>Your start looks right, although I think your speed equation is wrong. To continue, the FT has no time dependance so you can take the integral out.</p>
<p>$$G(u, v) = \int_0^T \mathcal F\{f(x-x_0, y-y_0)\} dt $$</p>
<p>$$ = F(u,v) \int_0^T e^{-2\pi i(x_0u + y_0v)} dt$$</p>
<p>Divide by $F$ to get the transfer fun... | 621 |
filtering | Extract signal from big gaussian noise | https://dsp.stackexchange.com/questions/16511/extract-signal-from-big-gaussian-noise | <p>I have signal, periodic with amplitude 10 with frequency about 10 kHz. It is hidden in Gaussian noise with standard deviation 100. Some idea how to extract periodic signal?
Thanks in advance.</p>
| <p>Rearrange the signal into a matrix containing one period in each row and average down the columns. </p>
| 622 |
filtering | How to design a filter with a certain magnitude response | https://dsp.stackexchange.com/questions/16781/how-to-design-a-filter-with-a-certain-magnitude-response | <p>I am trying to design a filter whose magnitude is the same as that of a given signal. The given signal is wind turbine noise, so it has significant low-frequency content. After designing the filter, I want to filter white Gaussian noise so as to create a model of wind turbine noise. The two signals, that is the orig... | <p>if you are only interested in designing a signal representing the wind turbine noise, you could just generate it from your magnitude. E.g., with your magnitude $A$ over frequency $f$ you can generate a random phase $\phi$ for each frequency and over a time $t$ and then add all together. Here a small code for illustr... | 623 |
filtering | difference between mean filter and order statistic filter | https://dsp.stackexchange.com/questions/24064/difference-between-mean-filter-and-order-statistic-filter | <p>I am working on my paper about comparing between mean filter and ordering statistics filter, The mean filter is contraharmonic mean filter and the ordering statistic filter is alphatrimmed mean filter. So, I compare contraharmonic mean filter and alphatrimmed mean filter</p>
<p>and i've read a slide presentation th... | <h3>Quick Answer</h3>
<p>The main difference of this filters is how it perform the operations.</p>
<h2>Mean Filter</h2>
<h3>Brief Description</h3>
<p>Mean filtering is a spatial filter, and it's a simple, intuitive and easy to implement method of smoothing images, i.e. reducing the amount of intensity variation bet... | 624 |
filtering | If a signal is added to another in the freq. domain, how to filter it out? | https://dsp.stackexchange.com/questions/24870/if-a-signal-is-added-to-another-in-the-freq-domain-how-to-filter-it-out | <p>I have two signals, $x$ and $y$. I know that
$F(x)=F(s)+F(n)$ and $F(y)=F(n)$, where $s$ is the 'clean' signal, $n$ is the added noise and $F$ donate Fourier Transform.</p>
<p>To obtain the clean signal, I am trying the following: $s=F^{-1}[F(x)-F(y)]$. Is there any better way that I should try?</p>
| 625 | |
filtering | In fourier space, how to apply transfer function with n frequencies to input data with m>>n frequencies | https://dsp.stackexchange.com/questions/29783/in-fourier-space-how-to-apply-transfer-function-with-n-frequencies-to-input-dat | <p>I have a transfer function in Fourier space with $N=2028$ frequencies $(\frac {0, 1}{(N\cdot dx)} \dots ) $</p>
<p>Where $dx = 0.1m$. </p>
<p>I need to apply this transfer function to a signal with 20000 samples (also $dx=0.1m$).
When I transform this signal to Fourier space I get 20000 frequencies.
So, the size... | <p>That is not correct. The frequency range is still the same with 20000 bins, the bins are just closer. What you need to do is:</p>
<ul>
<li>Apply a Window Function with lenght 2028 (such as Hamming Window) with an appropriate overlap between windows.</li>
<li>Fourier-transform each window.</li>
<li>Multiply each win... | 626 |
filtering | Practical examples of ARMA model | https://dsp.stackexchange.com/questions/35159/practical-examples-of-arma-model | <p>I am studying the Kalman filter and its basic implementation, and it was asked to use the filter to estimate a signal observed in noise
$$y(n) = x(n) + v(n)$$
where $v(n) \sim \mathcal{N}(0, \sigma^2)$ and $x(n)$ is modeled as an ARMA(2,2) process
$$x(n) = b_0 u(n) + b_1 u(n-1) - a_1 x(n-1) - a_2 x(n-2).$$ </p>
<p>... | <p>ARMA models are useful when you need to model a Signal plus Noise situation where the signal is an AR process and the noise models sensor noise. The overall model is an ARMA model.</p>
<p>See HL Van Trees, Detection, Estimation, and Modulation Theory, vol 4 Array Processing. He gives an example of a Spatial AR proc... | 627 |
filtering | Understanding the lowpass filtering of a digital signal | https://dsp.stackexchange.com/questions/36661/understanding-the-lowpass-filtering-of-a-digital-signal | <p>I do not have any background in Electrical Engineering and I have recently started a project which involves signals captured from sensors.</p>
<p>Lowpass filtering: The way I understand it is: The values below the <code>CUTOFF</code> are allowed to pass through, above the <code>CUTOFF</code> are simply filtered.</p... | <p>Any signal can be constructed from the sum of sinusoids of different frequencies (to within an arbitrarily small error). This reconstruction is unique and can be calculated with the Fourier transform.</p>
<p>When we talk about the various frequencies that comprise a signal, we are talking about these sinusoids of ... | 628 |
filtering | How do I eliminate line noise from USB microphone | https://dsp.stackexchange.com/questions/36725/how-do-i-eliminate-line-noise-from-usb-microphone | <p>I'm trying to record voice from a microphone into my laptop. Unfortunately, the laptop does not have a microphone jack, so I have to use the USB input. This doesn't present a problem when I record voice from my gaming headset, but when I record from the condenser microphone over USB I get a very pronounced line hu... | <p>I would suggest adding a device as like Xenyx 302USB (~50$) in your recording path.</p>
<p><strong>If it's just voice recording in question</strong> (and Windows based computer) then you could install <a href="https://sourceforge.net/projects/equalizerapo/" rel="nofollow noreferrer">EqualizerAPO</a> and prepare sui... | 629 |
filtering | Digital Lowpass butterworth filter with cut off 500Hz and sampling rate 1.25MSPS | https://dsp.stackexchange.com/questions/38120/digital-lowpass-butterworth-filter-with-cut-off-500hz-and-sampling-rate-1-25msps | <p>I am trying to simulate a distributed sensing system and I need to filter only frequencies lesser than 500 Hz(low pass filter) from acquired signal with sample rate 1250000 Samples/sec using below mentioned program:</p>
<pre><code> %Time specifications:
Fs = 1250000; % samples per second
dt ... | <p><strong>Solution</strong>: Take a lower order butterworth filter or sampling frequency</p>
<p><strong>Reason</strong>: As discussed <a href="https://www.kvraudio.com/forum/viewtopic.php?t=311413" rel="nofollow noreferrer">here</a>, a high order butterworth filter with a low (relative) cutoff frequency may be numeri... | 630 |
filtering | Do integration/differentiation processes work as simple filters? | https://dsp.stackexchange.com/questions/48584/do-integration-differentiation-processes-work-as-simple-filters | <p>How these processes are different from simple IIR 1 order filtering, FIR filters in terms of amplitude and phase characteristics?</p>
| <p>Yes, integration and differentiation can be linear filters.
You can start from <code>laplace properties</code> that say:</p>
<p>$ \int_{0}^{t} {x(t)dt} \longrightarrow \frac{X(s)}{s} \\ \frac{d}{dt}x(t) \longrightarrow sX(s) $</p>
<p>So you can find <code>transfer function</code> of integration and differentiation... | 631 |
filtering | What do poles do for a filter? | https://dsp.stackexchange.com/questions/49830/what-do-poles-do-for-a-filter | <p>What are the disadvantages of having too many poles?</p>
<p>Thanks.</p>
| <p>Poles in a filter come from recursions. Consider a discrete filter</p>
<p>$$y(k) = x(k) + \alpha y(k-1)$$</p>
<p>where $y(k)$ describes the output of the system, $x(k)$ the input and $y(k-1)$ the output of the system the sample before.</p>
<p>Now what the recursive part $y(k-1)$ does is that it feeds the system t... | 632 |
filtering | How to apply discrete filters to a signal | https://dsp.stackexchange.com/questions/59843/how-to-apply-discrete-filters-to-a-signal | <p>Let's say I have a signal like x[k] = [-20 -50 -30 50 30 -60 60 -60 60 10 5 10 5 5], and I want to apply a lowpass and a highpass filter to this signal (separately). For example the impusle response of the filters are as follows:</p>
<p>Lowpass: h[k] = [-1 2 6 2 -1], k = -1,0,...,3</p>
<p>Highpass: g[k] = [-1 2 -1... | <p>Another way to simply get your result for this kind of a problem (where <span class="math-container">$h[n]$</span> is very short) is to use the following method :</p>
<p>Let your output of the discrete convolution sum be <span class="math-container">$y[n]$</span> :
<span class="math-container">$$ y[n] = x[n] \star ... | 633 |
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