plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | vyoussofzadeh/CAMEG-master | inputdlg.m | .m | CAMEG-master/External functions/spm/private/inputdlg.m | 12,452 | utf_8 | e9d80a588d04401cefdb88a9ff95f996 | function Answer=inputdlg(Prompt, Title, NumLines, DefAns, Resize)
%INPUTDLG Input dialog box.
% ANSWER = INPUTDLG(PROMPT) creates a modal dialog box that returns user
% input for multiple prompts in the cell array ANSWER. PROMPT is a cell
% array containing the PROMPT strings.
%
% INPUTDLG uses UIWAIT to suspend ex... |
github | vyoussofzadeh/CAMEG-master | cfg_justify.m | .m | CAMEG-master/External functions/spm/private/cfg_justify.m | 4,781 | utf_8 | f35de815dab47aff40ab2987909d5f26 | function out = cfg_justify(varargin)
% CFG_JUSTIFY Justifies a text string
% OUT = CFG_JUSTIFY(N,TXT) justifies text string TXT to
% the length specified by N.
%
% OUT = CFG_JUSTIFY(OBJ,TXT), where OBJ is a handle to a 'listbox' style
% uicontrol, justifies text string TXT to the width of the OBJ in
% ch... |
github | vyoussofzadeh/CAMEG-master | listdlg.m | .m | CAMEG-master/External functions/spm/private/listdlg.m | 8,479 | utf_8 | 9e6dc823af689b0c265f2631948dbc5d | function [selection,value] = listdlg(varargin)
%LISTDLG List selection dialog box.
% [SELECTION,OK] = LISTDLG('ListString',S) creates a modal dialog box
% which allows you to select a string or multiple strings from a list.
% SELECTION is a vector of indices of the selected strings (length 1 in
% the single se... |
github | vyoussofzadeh/CAMEG-master | resolve_deps.m | .m | CAMEG-master/External functions/spm/@cfg_item/resolve_deps.m | 3,618 | utf_8 | 436b23723204757dca38afc10caccc02 | function [val, sts] = resolve_deps(item, cj)
% function [val, sts] = resolve_deps(item, cj)
% Resolve dependencies for an cfg item. This is a generic function that
% returns the contents of item.val{1} if it is an array of cfg_deps. If
% there is more than one dependency, they will be resolved in order of
% appearance... |
github | vyoussofzadeh/CAMEG-master | clickableLegend.m | .m | CAMEG-master/External functions/Other/clickableLegend.m | 7,280 | utf_8 | c76e8a2214087ff671f83e02aaf9645b | function varargout = clickableLegend(varargin)
% clickableLegend Interactive legend for toggling or highlighting graphics
%
% clickableLegend is a wrapper around the LEGEND function that provides
% interactive display toggling or highlighting of lines or patches in a MATLAB
% plot. It enables you to,
% * Toggle (hide/... |
github | cnzero/sEMG_SDK-master | ZC_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/ZC_feature.m | 439 | utf_8 | 86cb0b78a551c30dd85e6bc29cafd2c0 | %[ZC-zero crossing] feature
function feature = ZC_feature(data_TimeWindow)
DeadZone = 0;
data_size = length(data_TimeWindow);
feature = 0;
if data_size == 0
feature = 0;
else
for i=2:data_size
difference = data_TimeWindow(i) - data_TimeWindow(i-1);
multy = data_TimeWindow(i) * data_TimeWindow(i-1);... |
github | cnzero/sEMG_SDK-master | WL_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/WL_feature.m | 145 | utf_8 | 6873f57c99d763d9c2dd352bd0793c91 | %[WL-Waveform Length] feature
function feature = WL_feature(data_TimeWindow)
feature = sum(abs(diff(data_TimeWindow)))/length(data_TimeWindow);
|
github | cnzero/sEMG_SDK-master | WAMP_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/WAMP_feature.m | 377 | utf_8 | d175203c50d1ae4bb6addd68b3963cff | %-[WA-Willison Amplitude] feature
function feature = WAMP_feature(data_TimeWindow)
Threshold = 0;
data_size = length(data_TimeWindow);
feature = 0;
if data_size == 0
feature = 0;
else
for i=2:data_size
difference = data_TimeWindow(i) - data_TimeWindow(i-1);
if abs(difference)>Threshold
feature = feat... |
github | cnzero/sEMG_SDK-master | ARC_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/ARC_feature.m | 222 | utf_8 | 34a40af3f3a2b8e05dc53da692687659 | % ARC, Auto Regression Model coefficients.
% the first coefficient of ARC with order four.
function feature = ARC_feature(x)
order = 4;
cur_xlpc = real(lpc(x,order)');
feature = -cur_xlpc(order+1,:);
|
github | cnzero/sEMG_SDK-master | VAR_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/VAR_feature.m | 96 | utf_8 | d7e3fab6654800330e9848d96c8ca82d | % Variance - VAR
function feature = VAR_feature(data_TimeWindow)
feature = var(data_TimeWindow) |
github | cnzero/sEMG_SDK-master | SSC_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/SSC_feature.m | 529 | utf_8 | 0308343e33a3b9c6d2bf97f1de0ab37d | %[SSC-Slope Sign Change] feature
function feature = SSC_feature(data_TimeWindow)
DeadZone = 0;
data_size = length(data_TimeWindow);
feature = 0;
if data_size == 0
feature = 0;
else
for j=3:data_size
difference1 = data_TimeWindow(j-1) - data_TimeWindow(j-2);
difference2 = data_TimeWindow(j-1) - data_Time... |
github | cnzero/sEMG_SDK-master | RMS_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/RMS_feature.m | 116 | utf_8 | 6d4cb30228097912784ed9e1e2ecef53 | % [RMS-Root Mean Square]
function feature = RMS_feature(data_TimeWindow)
feature = sqrt(mean(data_TimeWindow.^2));
|
github | cnzero/sEMG_SDK-master | MAV_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/MAV_feature.m | 123 | utf_8 | 5dd3434c670e3aac277aad23c1a26be7 | % [MAV-Mean Absolute Value] feature
function feature = MAV_feature(data_TimeWindow)
feature = mean(abs(data_TimeWindow));
|
github | cnzero/sEMG_SDK-master | PSD_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/PSD_feature.m | 73 | utf_8 | 880f414aa348d872627256dbe3885ea8 | % Power Spectral Density, PSD
function feature = PSD_feature(data)
% 918 |
github | cnzero/sEMG_SDK-master | MAX_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/MAX_feature.m | 88 | utf_8 | 21f5d91c6d3635fe7033a0abd32310ef | % MAX - Maximum value
function feature = MAX_feature(data)
feature = max(abs(data)); |
github | cnzero/sEMG_SDK-master | Ceps_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/Ceps_feature.m | 560 | utf_8 | 5ec0bbc9364650343568c88b8e0c1d62 | % Cepstrum coefficients, Ceps
% Equation(1-11) in Xiong's Ph.D article.
function feature = Ceps_feature(data_TimeWindow, order)
arc = getar_lpcfeat(data_TimeWindow, order);
%size: orderx1
feature(1, 1) = -arc(1);
for l=2:order
total = 0;
for j=1:l-1
total = total + (1 - j/l)*arc(j)*feature(1, l-j);
feat... |
github | cnzero/sEMG_SDK-master | IAV_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/IAV_feature.m | 137 | utf_8 | f17a9824166eaed9605b6aa91debd016 | % $x^2+e^{\pi i}$
%[IAV-Integrated Absolute Value] feature
function feature = IAV_feature(data)
feature = sum(abs(data))/length(data);
|
github | cnzero/sEMG_SDK-master | NonZeroMedIndex_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/NonZeroMedIndex_feature.m | 567 | utf_8 | f2b83c2430316324750c96962ace29f3 | % Index of NonZeroMed (Ind)
function f = NonZeroMedIndex_feature(data)
data_nonzero = data(find(data ~=0));
data_sorted = sort(data_nonzero, 'ascend');
L = length(data_sorted);
L2 = (fix(L/2));
if mod(L, 2)==1
median_value = median(data_sorted);
f_logic = data_sorted==medi... |
github | cnzero/sEMG_SDK-master | MNF_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/MNF_feature.m | 380 | utf_8 | 5c7bf589c1b9364a7500c5074f6f7bcd | % Mean Frequency, MNF
function feature = MNF_feature(data_TimeWindow)
Window_L = length(data_TimeWindow);
power_spectral = abs(fft(data_TimeWindow, Window_L).^2)/Window_L;
L = length(power_spectral);
Fs = 2000; % Sampling frequency
f = Fs/2*linspace(0, 1, L/2)';
feature = meanfrequency(f, power_spectral(1:L/2));
... |
github | cnzero/sEMG_SDK-master | MDF_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/MDF_feature.m | 866 | utf_8 | 791b93430c2639aacdec046e343129a7 | function feature = MDF_feature(data_TimeWindow)
Window_L = length(data_TimeWindow);
power_spectral = abs(fft(data_TimeWindow, Window_L).^2)/Window_L;
L = length(power_spectral);
Fs = 2000; % Sampling frequency
f = Fs/2*linspace(0, 1, L/2)';
feature = medianfrequency(f, power_spectral(1:L/2));
% bisection search... |
github | cnzero/sEMG_SDK-master | NonZeroMed_feature.m | .m | sEMG_SDK-master/FeaturesExtraction/NonZeroMed_feature.m | 165 | utf_8 | c85e516f05ec2265d27e77d83ff38d71 | % Median value of non-zero value
% -- [NonZeroMed]
function f = NonZeroMed_feature(data)
data_nonzero = data(find(data ~= 0));
f = median(data_nonzero); |
github | cnzero/sEMG_SDK-master | PlotEMGsettings.m | .m | sEMG_SDK-master/acquisition/PlotEMGsettings.m | 1,642 | utf_8 | bf48bf7b2fa1218a614d31d589ed6baa | % function descriptions:
%
% Input:
% interfaceObject, a 1x3 cell of tcpip handles
% Output:
% figureHandleEMG
% plotHandlesEMG
function [figureHandleEMG, plotHandlesEMG] = PlotEMGsettings(interfaceObject, timerRefreshData)
% initiate the EMG figure
figureHandleEMG = figure('Name', 'EMG Data', ...
... |
github | cnzero/sEMG_SDK-master | init_Folder.m | .m | sEMG_SDK-master/acquisition/init_Folder.m | 862 | utf_8 | 215d76373bb4aacb7e9e99e6e0dd6e5c | % function description:
% get the folder name based on current time
% to create local folders.
% Input:
% Write:
% 1, Yes
% 0, No
% Output:
% folder_name,
function folder_name = init_Folder(Write)
folder_name = [];
if Write == 1
c = clock;
folder_name = [folder_name, ...
num2str(c(1)), ..... |
github | cnzero/sEMG_SDK-master | PlotACCsettings.m | .m | sEMG_SDK-master/acquisition/PlotACCsettings.m | 2,011 | utf_8 | 98961d9dde156e14ad14f4d8865f676e | % function descriptions:
%
% Input:
% interfaceObject, a 1x3 cell of tcpip handles
% Output:
% figureHandleEMG
% plotHandlesEMG
function [figureHandleACC, plotHandlesACC] = PlotACCsettings(interfaceObject, timerRefreshData)
% initiate the ACC figure
figureHandleACC = figure('Name', 'ACC Data', ...
... |
github | cnzero/sEMG_SDK-master | init_Connect.m | .m | sEMG_SDK-master/acquisition/init_Connect.m | 2,298 | utf_8 | 6c7137ba67b6c4792533439f23ce08d1 | % function descriptions:
% basic settings on the device, and acquire handles
% Input:
% -----Tinfo---
% InputBufferSize = 6400; [default]
% BytesAvailableFcnCountEMG = 1728; [default]
% BytesAvailableFcnCountACC = 384; [default]
% -----RPinfo---
% DebugPlot:
% 1: True, the origin result of Official SDK.
... |
github | cnzero/sEMG_SDK-master | Initiate.m | .m | sEMG_SDK-master/acquisition/Initiate.m | 1,015 | utf_8 | 4d3f56da88e725a69b379c3d49b9c975 | % function description
% get the acquiring data online and some parameters settings
% parameters settings
% -----Tinfo---
% InputBufferSize = 6400; [default]
% BytesAvailableFcnCountEMG = 1728; [default]
% BytesAvailableFcnCountACC = 384; [default]
% -----RPinfo---
% DebugPlot:
% 1: True, the origin ... |
github | cnzero/sEMG_SDK-master | sortVectorValue.m | .m | sEMG_SDK-master/Classification/sortVectorValue.m | 371 | utf_8 | dbc4b48ec7b9241a54ffddc8769e255e | % function description
% sorting eigenvectors with eigenvalues descending.
% Vector, matrix of eigenvectors
% Value, diagonal matrix of eigenvalues
function [new_Vector, new_Value] = sortVectorValue(Vector, Value)
val = diag(Value);
[new_val, idx] = sort(val, 'descend');
for i=1:size(Vector,2)
new_Vector(:, i) = ... |
github | cnzero/sEMG_SDK-master | LDA_Reduction.m | .m | sEMG_SDK-master/Classification/LDA_Reduction.m | 1,457 | utf_8 | 7c2616f9991c75bde46366d4ee655ef1 | % function description
% Input:
% [Samples_Cell], nx1-Cell, every cell is a supervised cluster.
% n, number of clusters or movement.
% [d], number of reduction dimension.
% Output:
% [centers], center of every conrresponding supervised cluster.
% nxd
% [LDA_matrix], the dimension-reduction matrix ... |
github | cnzero/sEMG_SDK-master | NearestDistance.m | .m | sEMG_SDK-master/MVC/NearestDistance.m | 672 | utf_8 | c9f9f5995162683d0b8bceb74eeffbd5 | % function description:
% find the nearest samples label
% Inputs:
% [samepleMatrix], 1xn, a sample matrix
% [reductCenters], every row 1xd is a clustering center position
% [reductMatrix], dimension-reduction matrix, nxd
% Output:
% [nLabel], number of nth row of [reductCenters]
% that is the nearest 2... |
github | cnzero/sEMG_SDK-master | Rawdata2SampleMatrix.m | .m | sEMG_SDK-master/MVC/Rawdata2SampleMatrix.m | 1,527 | utf_8 | 4b23d73c7112b08cc0d31e29e74639df | % function description:
% Input:
% [Rawdata], (2000t) X nCh,
% rawdata from selected sensor channels
% [featuresCell], a cell of strings, which are the name of selected features
% and also transform them as their features extraction functions' name
% [LW], the length of a features-extraction window
%... |
github | cnzero/sEMG_SDK-master | sortVectorValue.m | .m | sEMG_SDK-master/ReductionFunction/sortVectorValue.m | 371 | utf_8 | dbc4b48ec7b9241a54ffddc8769e255e | % function description
% sorting eigenvectors with eigenvalues descending.
% Vector, matrix of eigenvectors
% Value, diagonal matrix of eigenvalues
function [new_Vector, new_Value] = sortVectorValue(Vector, Value)
val = diag(Value);
[new_val, idx] = sort(val, 'descend');
for i=1:size(Vector,2)
new_Vector(:, i) = ... |
github | cnzero/sEMG_SDK-master | centering.m | .m | sEMG_SDK-master/ReductionFunction/centering.m | 488 | utf_8 | 9aa1553366b893e3f53ac55f8aedc1fd | % function description
% remove the whole meanValue from every cluster.
% Input: samples: 5x1-cell
% Output: new_samples: 5x1-cell,
% meanValue: the whole center, 1xn
function [new_samples, meanValue] = centering(samples)
Samples_Matrix = [samples{1}; ...
samples{2}; ...
samples{3}; ...
sample... |
github | cnzero/sEMG_SDK-master | test_builtin_PCA.m | .m | sEMG_SDK-master/ReductionFunction/test_builtin_PCA.m | 530 | utf_8 | 3ebab95c4e91deaf2501d13411824c95 | function test_builtin_PCA()
load hald;
coeff1 = pca(ingredients)
coeff2 = pca(Normalizing(ingredients))
coeff1/coeff2
function new_samples = Normalizing(samples)
% samples
% nxm
[n, m] = size(samples);
% n correspond to observations
% m correspond to variables, components.
% centering...
mean_values = m... |
github | cnzero/sEMG_SDK-master | ICA_Preprocessing.m | .m | sEMG_SDK-master/ReductionFunction/ICA_Preprocessing.m | 292 | utf_8 | 2b8f80e8b191844792a4ef157ee1c51b | % function description
% purpose: ICA decomposition
% Input: rawdata_matrix: nx4, with every column being one sensor's record
% Output: new_rawdata_matrx: nx4, with every column being one source information.
function new_rawdata_matrix = ICA_Preprocessing(rawdata_matrix)
% pass, pass |
github | cnzero/sEMG_SDK-master | FastICA_Reduction.m | .m | sEMG_SDK-master/ReductionFunction/FastICA_Reduction.m | 328 | utf_8 | fe59d12f14e3fce19b59405ffab31a69 | % function description
% Input:
% Samples_Matrix, nx1-Cell, every cell is a supervised cluster.
% Output:
% ICA_centers, center of every conrresponding supervised cluster.
% ICA_matrix, the dimension-reduction matrix with Independent Component Analysis.
function [ICA_centers, ICA_matrix] = ICA_Reduction(Samples... |
github | cnzero/sEMG_SDK-master | whitening.m | .m | sEMG_SDK-master/ReductionFunction/whitening.m | 307 | utf_8 | 0b0d3fb2df70d56cfe9eeae1704506b2 | % function description
% whitening the centered samples.
% Input: samples, 5x1-cell
% E, eigenvectors
% D, diagonal matrix of eigenvalues
% Output: new_samples, 5x1-cell
% whiteningMatrix
% dewhiteningMatrix
function [new_samples, whiteningMatrix, dewhiteningMatrix] = whitening(samples, E,D) |
github | cnzero/sEMG_SDK-master | LDA_Reduction.m | .m | sEMG_SDK-master/ReductionFunction/LDA_Reduction.m | 1,206 | utf_8 | 9f688a8cae568bf6f27f284643390442 | % function description
% Input:
% Samples_Matrix, nx1-Cell, every cell is a supervised cluster.
% d, number of reduction dimension.
% Output:
% centers, center of every conrresponding supervised cluster.
% LDA_matrix, the dimension-reduction matrix with Principle Component Analysis.
% Attention:
% LDA algor... |
github | cnzero/sEMG_SDK-master | PCA_Reduction.m | .m | sEMG_SDK-master/ReductionFunction/PCA_Reduction.m | 766 | utf_8 | 7f8232c29b180f90749ca38aa59adfa1 | % function description
% Input:
% Samples_Matrix, nx1-Cell, every cell is a supervised cluster.
% d, number of reduction dimension.
% Output:
% PCA_matrix, the dimension-reduction matrix with Principle Component Analysis.
function [PCA_centers, PCA_matrix, All_mean, All_var] = PCA_Reduction(Samples_Matrix, d)
... |
github | cnzero/sEMG_SDK-master | NMF_Reduction.m | .m | sEMG_SDK-master/ReductionFunction/NMF_Reduction.m | 643 | utf_8 | de6fa66dc3382394749fb74b00b86d01 | % function description
% Input:
% Samples_Matrix, nx1-Cell, every cell is a supervised cluster.
% d, number of reduction dimension.
% Output:
% NMF_matrix, the dimension-reduction matrix with Principle Component Analysis.
function [NMF_centers, NMF_matrix, All_mean, All_var] = NMF_Reduction(Samples_Matrix, d)
... |
github | cnzero/sEMG_SDK-master | ICA_normalization.m | .m | sEMG_SDK-master/ReductionFunction/ICA_normalization.m | 469 | utf_8 | 53dd19a7c09f2623f4706fb19f0083f6 | % function description
% let the covariance of Sample be EYE
function new_samples = ICA_normalization(Sample)
% centering
mean_value = mean(Sample, 1);
% 1xn
Sample_centering = Sample - repmat(mean_value, size(Sample, 1), 1);
% whitening
cov_var_value = cov(Sample_centering);
% nxn
[V, D] = eig(cov_var_value);... |
github | cnzero/sEMG_SDK-master | PCA_normalization.m | .m | sEMG_SDK-master/ReductionFunction/PCA_normalization.m | 433 | utf_8 | ec8680d85cefd9738ea55ba5b18afb90 | % function description
% every row of Sample matrix is normalized by [its own variance]
function [new_samples, mean_value, std_var_value] = PCA_normalization(Sample)
% centering
mean_value = mean(Sample, 1);
% 1xn
Sample_centering = Sample - repmat(mean_value, size(Sample, 1), 1);
% whitening
std_var_value = sqr... |
github | sigtrac2016/projetosigtrac-master | build_fmr.m | .m | projetosigtrac-master/ml/Fingerprints/build_fmr.m | 884 | utf_8 | d3c6f2778dc15eba7713bed9b2927c87 | % GENERATING FMR AND FNMR DATA
%
% Usage: build_fmr;
%
% Argument: Nothing
%
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% July 2013
function build_fmr( )
load('db.mat'); P=72;
fmr=zeros(100,P); fnmr=zeros(100,P);
for p=1:P
ffnew=ff{p};
... |
github | sigtrac2016/projetosigtrac-master | plot_data.m | .m | projetosigtrac-master/ml/Fingerprints/plot_data.m | 582 | utf_8 | ea5b85754c0fc9b43b54d8ba79f39a2a | % PLOT DATA
%
% Usage: plot_data( X,y );
%
% Argument: X - Data Points
% y - Plot Style (1 for blue, 2 for red, ...)
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% July 2013
function plot_data( X,y )
N=size(X,1); r=15;
hold on; axis equal;
pale={'b+... |
github | sigtrac2016/projetosigtrac-master | transform.m | .m | projetosigtrac-master/ml/Fingerprints/transform.m | 668 | utf_8 | 538bee1dec72f0fe31ed7584a01b5b7b | % COORDINATION TRANSFORM FUNCTION
%
% Usage: [ T ] = transform( M, i );
%
% Argument: M - Extracted Minutiae
% i - Index of reference minutia
%
% Returns: T - M with new coordinations
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% July 2013
... |
github | sigtrac2016/projetosigtrac-master | score.m | .m | projetosigtrac-master/ml/Fingerprints/score.m | 1,064 | utf_8 | 64f502df8df62ebf42ed251d2c42de6b | % TRANSFORMED MINUTIAE MATCHING SCORE
%
% Usage: [ si ] = score( T1, T2 );
%
% Argument: T1 - First Transformed Minutiae
% T2 - Second Transformed Minutiae
%
% Returns: sm - Similarity Measure
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% Ju... |
github | sigtrac2016/projetosigtrac-master | ext_finger.m | .m | projetosigtrac-master/ml/Fingerprints/ext_finger.m | 18,420 | utf_8 | 4c00abbd202fac34da6e4d99dcf2d0fe | % EXTRACTING FEATURE FROM A FINGERPRINT IMAGE
%
% Usage: [ ret ] = ext_finger( img, display_flag );
%
% Argument: img - FingerPrint Image
% display_flag
%
% Returns: ret - Minutiae
% Adapted from Joshua Abraham, "Fingerprint Matching using A Hybrid
% Shape and Orientation Descriptor", ... |
github | sigtrac2016/projetosigtrac-master | transform2.m | .m | projetosigtrac-master/ml/Fingerprints/transform2.m | 635 | utf_8 | 405769b0cbbe861575e4691f3badac2c | % COORDINATION TRANSFORM FUNCTION
%
% Usage: [ Tnew ] = transform2( T, alpha );
%
% Argument: T - Transformed Minutiae
% alpha - Rotation angle
%
% Returns: Tnew - T with new coordinations
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% July ... |
github | sigtrac2016/projetosigtrac-master | match.m | .m | projetosigtrac-master/ml/Fingerprints/match.m | 1,311 | utf_8 | 622d954d3d2b500464325be3011ba709 | % FINGERPRINT MATCHING SCORE
%
% Usage: [ S ] = match( M1, M2, display_flag );
%
% Argument: M1 - First Minutiae
% M2 - Second Minutiae
% display_flag
%
% Returns: S - Similarity Measure
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%... |
github | sigtrac2016/projetosigtrac-master | f_enhance.m | .m | projetosigtrac-master/ml/Fingerprints/f_enhance.m | 1,247 | utf_8 | fee32b8a5cde0420545220893195fb9f | % ENHANCING FINGERPRINT IMAGE
%
% Usage: [ binim, mask, cimg, cimg2, orient_img, orient_img_m ] =
% ... f_enhance( img );
%
% Argument: img - FingerPrint Image
%
% Returns: binim - binary image
% mask - binary mask
% cimg1,2 - coherence image
% oim... |
github | sigtrac2016/projetosigtrac-master | build_db.m | .m | projetosigtrac-master/ml/Fingerprints/build_db.m | 717 | utf_8 | f80a57e4513153ae05e379d4f2be0eba | % BUILDING FINGERPRINT MINUTIAE DATABASE
%
% Usage: build_db(ICount, JCount);
%
% Argument: ICount - Number of FingerPrints
% JCount - Number of Images Per FingerPrint
%
% Vahid. K. Alilou
% Department of Computer Engineering
% The University of Semnan
%
% July 2013
function build_db(... |
github | sigtrac2016/projetosigtrac-master | ridgefreq.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/ridgefreq.m | 2,993 | utf_8 | 4d6730ff43c035f5969cb99df64ef76c | % RIDGEFREQ - Calculates a ridge frequency image
%
% Function to estimate the fingerprint ridge frequency across a
% fingerprint image. This is done by considering blocks of the image and
% determining a ridgecount within each block by a call to FREQEST.
%
% Usage:
% [freqim, medianfreq] = ridgefreq(im, mask, orienti... |
github | sigtrac2016/projetosigtrac-master | smoothen_orientation_image.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/smoothen_orientation_image.m | 1,058 | utf_8 | 8093fe05f83b5e1419810dd2e28fd5df | %------------------------------------------------------------------------
%smoothen_orientation_image
%smoothens the orientation image through vectorial gaussian filtering
%Usage:
%new_oimg = smoothen_orientation_image(oimg)
%oimg - orientation image
%new_oimg - filtered orientation image
%Contact:
% ssc5@eng.buf... |
github | sigtrac2016/projetosigtrac-master | freqest.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/freqest.m | 3,640 | utf_8 | d637be7a052bf46d9d575431c65542ee | % FREQEST - Estimate fingerprint ridge frequency within image block
%
% Function to estimate the fingerprint ridge frequency within a small block
% of a fingerprint image. This function is used by RIDGEFREQ
%
% Usage:
% freqim = freqest(im, orientim, windsze, minWaveLength, maxWaveLength)
%
% Arguments:
% im... |
github | sigtrac2016/projetosigtrac-master | compute_coherence.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/compute_coherence.m | 1,072 | utf_8 | b1924a2e37a56cd2773c5f51ca1f3733 | %------------------------------------------------------------------------
%compute_coherence
%Computes the coherence image.
%Usage:
%[cimg] = compute_coherence(oimg)
%oimg - orientation image
%cimg - coherence image(0-low coherence,1-high coherence)
%Contact:
% ssc5@eng.buffalo.edu
% www.eng.buffalo.edu/~ssc5
%Ref... |
github | sigtrac2016/projetosigtrac-master | test_bifurcation.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/test_bifurcation.m | 5,940 | utf_8 | 40c9618b8dd39c195d7145cc178fac10 |
% Returns if the single ridge in a bifurcation is
% the going the same direction as the orientation (res=3)
% or in in the opposite (res=2)
function [res, progress, sx, sy, angle] = test_bifurcation(img, x, y, o, core_x, core_y)
iax = 0; iay = 0; ibx = 0; iby = 0; icx = 0; icy = 0;
progress = 1;
path_len =... |
github | sigtrac2016/projetosigtrac-master | fft_enhance_cubs.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/fft_enhance_cubs.m | 10,655 | utf_8 | 835562cdb17e381bf51754b639bee6bd | %--------------------------------------------------------------------------
%fft_enhance_cubs
%enhances the fingerprint image
%syntax:
%[oimg,fimg,bwimg,eimg,enhimg] = fft_enhance_cubs(img, BLKSZ)
%oimg - [OUT] block orientation image(can be viewed using
% view_orientation_image.m)
%fimg - [OUT] block frequen... |
github | sigtrac2016/projetosigtrac-master | ridgefilter.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/ridgefilter.m | 4,774 | utf_8 | 4b17d2abd1eed16258daac35442135d7 | % RIDGEFILTER - enhances fingerprint image via oriented filters
%
% Function to enhance fingerprint image via oriented filters
%
% Usage:
% newim = ridgefilter(im, orientim, freqim, kx, ky, showfilter)
%
% Arguments:
% im - Image to be processed.
% orientim - Ridge orientation image, obtained fr... |
github | sigtrac2016/projetosigtrac-master | ridgesegment.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/ridgesegment.m | 2,321 | utf_8 | e33f2fd996cf9fceef31670955f9ceaf | % RIDGESEGMENT - Normalises fingerprint image and segments ridge region
%
% Function identifies ridge regions of a fingerprint image and returns a
% mask identifying this region. It also normalises the intesity values of
% the image so that the ridge regions have zero mean, unit standard
% deviation.
%
% This function... |
github | sigtrac2016/projetosigtrac-master | smoothen_frequency_image.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/smoothen_frequency_image.m | 2,272 | utf_8 | 04c4c626cb22ecf4a977b1cc3b8bca7d | %------------------------------------------------------------------------
%smoothen_frequency_image
%smoothens the frequency image through a process of diffusion
%Usage:
%new_oimg = smoothen_frequency_image(fimg,RLOW,RHIGH,diff_cycles)
%fimg - frequency image image
%nimg - filtered frequency image
%RLOW ... |
github | sigtrac2016/projetosigtrac-master | angular_filter_bank.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/angular_filter_bank.m | 2,688 | utf_8 | 8238ba0a2edd63f5144ea4101b5fe63c | %----------------------------------------------------------
%angular_filter_bank
%precomputes angular filter bank and also generates a C
%header file with filter coefficients. The matlab variable
%angf is stored in file 'angular_filters.mat' and the C
%variables are stored in 'angular_fiter.h'.
%There are TSTEPS numbe... |
github | sigtrac2016/projetosigtrac-master | ridgeorient.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/ridgeorient.m | 4,185 | utf_8 | b7f22f3e806dec0eb1cff6b387925a11 | % RIDGEORIENT - Estimates the local orientation of ridges in a fingerprint
%
% Usage: [orientim, reliability] = ridgeorientation(im, gradientsigma,...
% blocksigma, ...
% orientsmoothsigma)
%
% Arguments: im - A nor... |
github | sigtrac2016/projetosigtrac-master | p.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/p.m | 712 | utf_8 | d22a1e45b88d49381bb6244a70ca06f9 | %-----Sub functions-------
function [j,X, Y] = p(img, x, y, i)
% get pixel value based on chart:
% 4 | 3 | 2
% 5 | | 1
% 6 | 7 | 8
switch (i)
case {1, 9}
Y=y;
X=x+1;
j = img(y, x + 1);
case 2
Y=y-1;
X=x+1;
j = img(y - 1, x + 1);
case 3
Y=y-1;
... |
github | sigtrac2016/projetosigtrac-master | normalise.m | .m | projetosigtrac-master/ml/Fingerprints/FExtraction/normalise.m | 2,313 | utf_8 | 22ce310bf3c2aa0719e98315b0dad3b1 | % NORMALISE - Normalises image values to 0-1, or to desired mean and variance
%
% Usage:
% n = normalise(im)
%
% Offsets and rescales image so that the minimum value is 0
% and the maximum value is 1. Result is returned in n. If the image is
% colour the image is converted to HSV and the value/intensity c... |
github | kshitijgoel007/AUVForwardDynamics-master | forwarddynamics2.m | .m | AUVForwardDynamics-master/forwarddynamics2.m | 9,045 | utf_8 | 55cfd5ca6e2d2e916b13be7f1711512a | % Forward Dynamics Model NPS AUV II (Healy and Lienhard 1993)
% * Advisor : Prof Vishwanath Nagarajan
% * Department of Ocean Engineering and Naval Architecture, *IIT Kharagpur*
% * *Autonomous Underwater Vehicle Team, IIT Kharagpur*
%
% function dX = forwarddynamics2(t, X)
% Function containing 6DOF equations of bot... |
github | kshitijgoel007/AUVForwardDynamics-master | accelerometer_model.m | .m | AUVForwardDynamics-master/sensorModels/accelerometer_model.m | 2,184 | utf_8 | 3b0ac2eba4b7e34b4e8f8f1d1d337385 | % Three axis Accelerometer model - [22-12-2016]
% https://github.com/ethz-asl/kalibr/wiki/IMU-Noise-Model (some issue with
% noise density)
% An introduction to inertial navigation by Oliver J. Woodman
% A comparison between different error modelling of MEMS applied to GPS/INS
% integerated system
function [a_meas , a... |
github | kshitijgoel007/AUVForwardDynamics-master | integration2.m | .m | AUVForwardDynamics-master/utils/integration2.m | 2,636 | utf_8 | 2de52c4aebffe436f8838742b8ba2b46 |
function I=integration2(X)
k=0:(5.3/9):5.3;
u = X(1);
v = X(2);
w = X(3);
p = X(4);
q = X(5);
r = X(6);
syms x;
h=[2*sqrt(.0544*(x+2.65)),.42,.545*(5.26-(x-2.65))];
b=[2*sqrt(.14694*(x+2.65)),.69,.896*(5.26-(x-2.65))];
Ucf=sqrt((v+(x-2.65)*r)^2+(w-(x-2.65)*q)^2);
Ucf1=@(x)Ucf;
Cdy=.5;
Cdz=.6;
sway=zeros(1,10);
hea... |
github | kshitijgoel007/AUVForwardDynamics-master | stateEstimation.m | .m | AUVForwardDynamics-master/stateEstimation/stateEstimation.m | 1,554 | utf_8 | 74a39853e86c8e5d05bc896809a4cee8 | % Reference for euler angles and velocity, position integeration
% http://www.chrobotics.com/library/understanding-euler-angles
% http://www.chrobotics.com/library/accel-position-velocity
function [X_est, P_est] = stateEstimation(A, tinc)
% Estimated states [ pos, euler_angles, velocity] %
%% Get these params from d... |
github | kshitijgoel007/AUVForwardDynamics-master | Runge_Kutta_solver.m | .m | AUVForwardDynamics-master/Solvers/Runge_Kutta_solver.m | 14,815 | utf_8 | 87cfd72b62678debfa9b0b91771c84f7 |
function Y=Runge_Kutta_solver(caseNo,timespan,X)
% Function for solving 6DOF equations using 1st order euler method
%
% INPUT : caseno : index no of the type of maneuver to be performed
% botCoordinatesInbodyFrame : 3185X3 matrix containing (x,y,z)
% co... |
github | kshitijgoel007/AUVForwardDynamics-master | euler.m | .m | AUVForwardDynamics-master/Solvers/euler.m | 1,921 | utf_8 | 9ba24db7d133fb433942d05721e68f02 |
function Y=euler(forwarddynamics2,timespan,X, ord_defl,caseNo)
% Function for solving 6DOF equations using 1st order euler method
h = diff(timespan);% for obtaining time step
dt = h(1);
Y = zeros(length(timespan),length(X)+1);
Y(:,1) = timespan(:);
Y(1,2:end) = X(:);
% initialising disturbance function
D = zeros(l... |
github | kshitijgoel007/AUVForwardDynamics-master | eulerFirstOrder.m | .m | AUVForwardDynamics-master/Solvers/eulerFirstOrder.m | 2,321 | utf_8 | a408e44e7d01af67af66a6b836efd160 |
function Y=eulerFirstOrder(forwarddynamics2,timespan,X, ord_defl,caseNo)
% Function for solving 6DOF equations using 1st order euler method
h = diff(timespan);% for obtaining time step
dt = h(1);
Y = zeros(length(timespan),length(X)+7);
Y(:,1) = timespan(:);
Y(1,2:end -6) = X(:);
% initialising disturbance functi... |
github | kshitijgoel007/AUVForwardDynamics-master | zigzag.m | .m | AUVForwardDynamics-master/test/zigzag.m | 1,080 | utf_8 | ecc117fa190ded257ff5d50513425a08 | %script for testing zig-zag
function zigzag()
close all;
t=0:.1:50;
dt=.1;
global Y;
%MAT FILE CONTAING PROPERTIES OF BOT
geoprop;
X=zeros(18,1);
X(1)=1;
Y=zeros(length(t),length(X)+1);
%first column stores time
Y(1,1)=0;
%INITIAL VALUES SAVED IN Y
for i=1:length(X)
Y(... |
github | kshitijgoel007/AUVForwardDynamics-master | zigzagvert_bp_bs.m | .m | AUVForwardDynamics-master/test/zigzagvert_bp_bs.m | 2,052 | utf_8 | f52590f9a04fcf579b649ee487d18e50 | %script for testing zig-zag
function zigzagvert_bp_bs(tend)
close all;
t=0:.1:tend;
dt=.1;
global Y del_bp del_bs
%MAT FILE CONTAING PROPERTIES OF BOT
geoprop;
r2d = 180/pi;
X=zeros(18,1);
X(1)=1; % initial surge velocity
Y=zeros(length(t),length(X)+1);
%first column stores time
Y(1,1)=0; ... |
github | kshitijgoel007/AUVForwardDynamics-master | zigzagvert.m | .m | AUVForwardDynamics-master/test/zigzagvert.m | 1,755 | utf_8 | afaf39b11d05dbedafb3a94ce53ec699 | %script for testing zig-zag
function zigzagvert(tend)
close all;
t=0:.1:tend;
dt=.1;
global Y;
%MAT FILE CONTAING PROPERTIES OF BOT
geoprop;
X=zeros(18,1);
X(1)=1;
Y=zeros(length(t),length(X)+1);
%first column stores time
Y(1,1)=0;
%INITIAL VALUES SAVED IN Y
for i=1:length... |
github | ebakstein/sigInspect-master | sigInspect.m | .m | sigInspect-master/sigInspect.m | 92,117 | utf_8 | 38009c1fdbc006b34a12147fbfedbfbd | function varargout = sigInspect(varargin)
% SIGINSPECT - a GUI for signal inspection and annotation
%
% USE:
% 1 - single multi-channel signal (matrix as input)
% C x N matrix (C = channels, N = samples )
% sigInspect(signal, samplingFreq); % signal: chan. in rows, samples in columns
%
% 2 - multiple signals (cell ar... |
github | ebakstein/sigInspect-master | sigInspectOverview.m | .m | sigInspect-master/sigInspectOverview.m | 8,044 | utf_8 | 5138bde63791ca83676d0e4c5080e7da | function varargout = sigInspectOverview(varargin)
% SIGINSPECTOVERVIEW MATLAB code for sigInspectOverview.fig
% SIGINSPECTOVERVIEW, by itself, creates a new SIGINSPECTOVERVIEW or raises the existing
% singleton*.
%
% H = SIGINSPECTOVERVIEW returns the handle to a new SIGINSPECTOVERVIEW or the handle to
%... |
github | ebakstein/sigInspect-master | sigInspectComputeFeatures.m | .m | sigInspect-master/sigInspectComputeFeatures.m | 29,357 | utf_8 | 19d1a805ea78bca53e7ed928db9df93e | function [featVals featNames] = sigInspectComputeFeatures(segment, featNames, samplingFreq)
% [featVals featNames] = sigInspectComputeFeatures(segment, featNames)
% compute vector of features for MER artifact detection on signal segment
% IN
% segment - signal segment (multi-channel also supported)
% fe... |
github | ebakstein/sigInspect-master | sigInspectAutoLabel.m | .m | sigInspect-master/sigInspectAutoLabel.m | 7,476 | utf_8 | 1ee77e11187d591d3a900b664e9cf9ec | function annotation = sigInspectAutoLabel(interfSignalOrPath, pathToSave, samplingFreq, method, varargin)
% annot = sigInspectAutoLabel(iterfSignalOrPath, pathToSave, samplingFreq, method, params)
% label all signals from provided cell array or interface using pre-learned
% classifier, return/save annot
%
%... |
github | galad-loth/HSI-Classification-master | MLRTrainAL.m | .m | HSI-Classification-master/smlr/MLRTrainAL.m | 3,072 | utf_8 | 9f74e37ce8a40e5b7da2649b589f66fd | function [w,L] = MLRTrainAL(x,y, lambda,beta,MMiter)
% Sparse Multinomial Logistic Regression
%
% Implements a block Gauss Seidel algorithm for fast solution of
% the SMLR introduced in Krishnapuram et. al, IEEE TPMI, 2005 (eq. 12)
%
% -- Input Parameters ----------------
%
% x -> training set (eac... |
github | galad-loth/HSI-Classification-master | GetGLCMFeat.m | .m | HSI-Classification-master/img_process/GetGLCMFeat.m | 4,118 | utf_8 | 2496b8083fa6360d3329f9d87703ce90 | function feat_glcm=GetGLCMFeat(img_q, offset,win_size)
% Compute GLCM texture feature of the input image
% Input:
% img_q: quantified img, the graylevel should range from 0 to max_gray_lavel
% offset: the spatial offset for compute the co-occurance matrix
% win_size: the window siz... |
github | galad-loth/HSI-Classification-master | GetGaborFeat.m | .m | HSI-Classification-master/img_process/GetGaborFeat.m | 1,537 | utf_8 | 44eca579d7dc8ea61b200ffbbf36dbdd | function feat_gbr=GetGaborFeat(img,lambda,theta,var_xy)
%Extract Gabor texture feature of the input image
%Example:
% lambda=[0,1/2,1/3];
% theta=[0,45,90,135]/180*pi;
% var_xy=[3,3;7,7;11,11;15,15];
% feat_gbr=GetGaborFeat(img,lambda,theta,var_xy)
% 2016-10-1... |
github | galad-loth/HSI-Classification-master | GetMaxTree.m | .m | HSI-Classification-master/img_process/GetMaxTree.m | 2,020 | utf_8 | f863ae24c3610dea9888dd3587048c00 | function max_tree=GetMaxTree(img,graylevel_list)
% Construct the Max-Tree for extracting Attribute Profile
%2016-10-20, jlfeng
[nr,nc,nd]=size(img);
if (nd>1)
error('Scalar value img is expected.');
end
num_obj=1;
label_obj=ones(nr,nc);
max_tree=struct('level',0,'area',0,'std',[],'hu_moment1',[],'idx_pix',... |
github | galad-loth/HSI-Classification-master | GetAP.m | .m | HSI-Classification-master/img_process/GetAP.m | 2,937 | utf_8 | 7836350303a995767f40ce407b6558a4 | function attr_profile=GetAP(img,graylevel_list, max_tree, attr_name, vec_thresh, prun_strategy)
% Extract Attribute Profile of the input image
%2016-10-20, jlfeng
if ~isfield(max_tree(1),attr_name)
error('The attribue does not exist!');
end
[nr,nc]=size(img);
num_thresh=length(vec_thresh);
attr_profile=zero... |
github | dgallichan/retroMoCoBox-master | pdftops.m | .m | retroMoCoBox-master/export_fig/pdftops.m | 3,574 | utf_8 | 92ff676904575e16046dfff010b4e145 | function varargout = pdftops(cmd)
%PDFTOPS Calls a local pdftops executable with the input command
%
% Example:
% [status result] = pdftops(cmd)
%
% Attempts to locate a pdftops executable, finally asking the user to
% specify the directory pdftops was installed into. The resulting path is
% stored for future refere... |
github | dgallichan/retroMoCoBox-master | crop_borders.m | .m | retroMoCoBox-master/export_fig/crop_borders.m | 4,703 | utf_8 | 918d1b232ba972d5dcfd0784147e6516 | function [A, vA, vB, bb_rel] = crop_borders(A, bcol, padding, crop_amounts)
%CROP_BORDERS Crop the borders of an image or stack of images
%
% [B, vA, vB, bb_rel] = crop_borders(A, bcol, [padding])
%
%IN:
% A - HxWxCxN stack of images.
% bcol - Cx1 background colour vector.
% padding - scalar indicating how much... |
github | dgallichan/retroMoCoBox-master | isolate_axes.m | .m | retroMoCoBox-master/export_fig/isolate_axes.m | 4,721 | utf_8 | 253cd7b7d8fc7cb00d0cc55926f32de5 | function fh = isolate_axes(ah, vis)
%ISOLATE_AXES Isolate the specified axes in a figure on their own
%
% Examples:
% fh = isolate_axes(ah)
% fh = isolate_axes(ah, vis)
%
% This function will create a new figure containing the axes/uipanels
% specified, and also their associated legends and colorbars. The objects
%... |
github | dgallichan/retroMoCoBox-master | im2gif.m | .m | retroMoCoBox-master/export_fig/im2gif.m | 6,048 | utf_8 | 5a7437140f8d013158a195de1e372737 | %IM2GIF Convert a multiframe image to an animated GIF file
%
% Examples:
% im2gif infile
% im2gif infile outfile
% im2gif(A, outfile)
% im2gif(..., '-nocrop')
% im2gif(..., '-nodither')
% im2gif(..., '-ncolors', n)
% im2gif(..., '-loops', n)
% im2gif(..., '-delay', n)
%
% This function converts a mu... |
github | dgallichan/retroMoCoBox-master | read_write_entire_textfile.m | .m | retroMoCoBox-master/export_fig/read_write_entire_textfile.m | 924 | utf_8 | 779e56972f5d9778c40dee98ddbd677e | %READ_WRITE_ENTIRE_TEXTFILE Read or write a whole text file to/from memory
%
% Read or write an entire text file to/from memory, without leaving the
% file open if an error occurs.
%
% Reading:
% fstrm = read_write_entire_textfile(fname)
% Writing:
% read_write_entire_textfile(fname, fstrm)
%
%IN:
% fname - Pathn... |
github | dgallichan/retroMoCoBox-master | pdf2eps.m | .m | retroMoCoBox-master/export_fig/pdf2eps.m | 1,471 | utf_8 | a1f41f0c7713c73886a2323e53ed982b | %PDF2EPS Convert a pdf file to eps format using pdftops
%
% Examples:
% pdf2eps source dest
%
% This function converts a pdf file to eps format.
%
% This function requires that you have pdftops, from the Xpdf suite of
% functions, installed on your system. This can be downloaded from:
% http://www.foolabs.com/xpdf ... |
github | dgallichan/retroMoCoBox-master | print2array.m | .m | retroMoCoBox-master/export_fig/print2array.m | 9,369 | utf_8 | ca18a1e6c5a944b591a0557bd69f1c2c | function [A, bcol] = print2array(fig, res, renderer, gs_options)
%PRINT2ARRAY Exports a figure to an image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% A = print2array(figure_handle... |
github | dgallichan/retroMoCoBox-master | append_pdfs.m | .m | retroMoCoBox-master/export_fig/append_pdfs.m | 2,678 | utf_8 | 949c7c4ec3f5af6ff23099f17b1dfd79 | %APPEND_PDFS Appends/concatenates multiple PDF files
%
% Example:
% append_pdfs(output, input1, input2, ...)
% append_pdfs(output, input_list{:})
% append_pdfs test.pdf temp1.pdf temp2.pdf
%
% This function appends multiple PDF files to an existing PDF file, or
% concatenates them into a PDF file if the output fi... |
github | dgallichan/retroMoCoBox-master | using_hg2.m | .m | retroMoCoBox-master/export_fig/using_hg2.m | 1,002 | utf_8 | b1620dd31f4d0b8acea2723e354a3518 | %USING_HG2 Determine if the HG2 graphics engine is used
%
% tf = using_hg2(fig)
%
%IN:
% fig - handle to the figure in question.
%
%OUT:
% tf - boolean indicating whether the HG2 graphics engine is being used
% (true) or not (false).
% 19/06/2015 - Suppress warning in R2015b; cache result for improved per... |
github | dgallichan/retroMoCoBox-master | eps2pdf.m | .m | retroMoCoBox-master/export_fig/eps2pdf.m | 8,435 | utf_8 | 95432e4216ee24df69e7e5720c6c4039 | function eps2pdf(source, dest, crop, append, gray, quality, gs_options)
%EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, dest, crop... |
github | dgallichan/retroMoCoBox-master | ghostscript.m | .m | retroMoCoBox-master/export_fig/ghostscript.m | 7,706 | utf_8 | 92dbafb8d4fb243cae8716c6ecb0bbe5 | function varargout = ghostscript(cmd)
%GHOSTSCRIPT Calls a local GhostScript executable with the input command
%
% Example:
% [status result] = ghostscript(cmd)
%
% Attempts to locate a ghostscript executable, finally asking the user to
% specify the directory ghostcript was installed into. The resulting path
% is s... |
github | dgallichan/retroMoCoBox-master | fix_lines.m | .m | retroMoCoBox-master/export_fig/fix_lines.m | 6,290 | utf_8 | 8437006b104957762090e3d875688cb6 | %FIX_LINES Improves the line style of eps files generated by print
%
% Examples:
% fix_lines fname
% fix_lines fname fname2
% fstrm_out = fixlines(fstrm_in)
%
% This function improves the style of lines in eps files generated by
% MATLAB's print function, making them more similar to those seen on
% screen. Grid ... |
github | dgallichan/retroMoCoBox-master | spm12_realign_parfor.m | .m | retroMoCoBox-master/fatnavtools/spm12_realign_parfor.m | 17,270 | utf_8 | 6caf6c354d0735d92452d329e3efae3b | function P = spm12_realign_parfor(P,flags)
% Estimation of within modality rigid body movement parameters
% FORMAT P = spm_realign(P,flags)
%
% P - char array of filenames
% All operations are performed relative to the first image.
% ie. Coregistration is to the first image, and resampling
% ... |
github | dgallichan/retroMoCoBox-master | fftn_fast.m | .m | retroMoCoBox-master/mirt_nufft/fftn_fast.m | 2,534 | utf_8 | d047a5ac60224a948bc9e5e1e8190298 | function Xs = fftn_fast(xs, ns)
%function Xs = fftn_fast(xs, ns)
%|
%| For some reason, in matlab versions before about 7.4 (R2007a),
%| matlab's fftn routine was suboptimal for the case of 2D FFTs,
%| at least on some machines.
%| The improvement herein was found by Hugo Shi.
%| After 7.4, fftn worked fine so this ro... |
github | dgallichan/retroMoCoBox-master | ir_sinc_nopi.m | .m | retroMoCoBox-master/mirt_nufft/ir_sinc_nopi.m | 786 | utf_8 | a988e7c3342459438bdcb60165e16a06 | function y = ir_sinc_nopi(x)
%function y = ir_sinc_nopi(x)
%|
%| no pi version of "sinc" function, because matlab's sinc() is in a toolbox
%|
%| Copyright 2001-12-8, Jeff Fessler, University of Michigan
%| Modified by M Allison to not have a pi.
if nargin < 1, help(mfilename), error(mfilename), end
if streq(x, 'test'... |
github | dgallichan/retroMoCoBox-master | nufft_init.m | .m | retroMoCoBox-master/mirt_nufft/nufft_init.m | 9,743 | utf_8 | 646e7bfaee97c079811a6fb2461b656e | function st = nufft_init(om, Nd, Jd, Kd, varargin)
%function st = nufft_init(om, Nd, Jd, Kd, [n_shift,] ...)
%|
%| Initialize structure for d-dimension NUFFT using KB interpolator,
%| particularly the interpolation matrix in sparse format.
%| caution: this routine can require a lot of memory!
%| in
%| om [M d] "digita... |
github | dgallichan/retroMoCoBox-master | dtft.m | .m | retroMoCoBox-master/mirt_nufft/dtft.m | 3,771 | utf_8 | 3883bdb38c25797eb59eb4ef02c855eb | function X = dtft(x, omega, varargin)
%function X = dtft(x, omega [,options])
%|
%| Compute d-dimensional DTFT of signal x at frequency locations omega
%|
%| in
%| x [(Nd) L] signal values
%| omega [M dd] frequency locations (radians), dd = numel(Nd)
%|
%| option
%| 'n_shift' [dd 1] use [0:N-1]-n_shift (default [0 ..... |
github | dgallichan/retroMoCoBox-master | newfft.m | .m | retroMoCoBox-master/mirt_nufft/newfft.m | 18,071 | utf_8 | e0b645a8738bfaf0736af7fa463349d3 | function st = newfft(om_in, Nd_in, varargin)
%function st = newfft(om, Nd, [options])
%|
%| New version of NUFFT (pun intended) that uses real interpolation kernels.
%| (The original NUFFT code used complex interpolation needlessly.)
%|
%| This returns a "strum" object with methods for both forward and adjoint
%| d-di... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.