text stringlengths 8 6.12M |
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function mat=reverse_diag(n)
a=zeros(n);
a(1:n+1:n^2)=1;
mat = flip(a,2);
%D(n:max([1,n-1]):max([n,n^2-1])) = 1; |
function juice_two_derivative2
close all;
clear all;
fs = 500;%采样率
%gold_standard = load('D:\zhaorui_2014\code\New_gold_standard.mat');%金标准
%raw_data = dir('D:\zhaorui_2014\data_change');
%raw_path = 'D:\zhaorui_2014\data_change\';
raw_data = dir('D:\spindle\two_order_derivative\data\');
raw_path = 'D:\spindle\two_orde... |
function z=zad1_redlich_kwong_clean(p,t,pc,tc)
%t=temperatura [K], p=ciśnienie [Pa]
r=8.3144;u=1;w=2;
a=0.42748*r^2*tc^2.5/pc/t^0.5;
b=0.0866*r*tc/pc;
A=a*p/r^2/t^2;
B=b*p/r/t;
z=roots([1,-1-B+u*B,A+w*B^2-u*B-u*B^2,-A*B-w*B^2-w*B^3]);
|
%% ------------------------------------------------------------------------%
% EE 569 Homework #3
% Date: Nov. 1, 2015
% Name: Faiyadh Shahid
% ID: 4054-4699-70
% Email: fshahid@usc.edu
%------------------------------------------------------------------------%
close all; clear all; clc;
%% Reading the file
row= 275; co... |
function I = polydefint(p,a,b)
%% POLYDEFINT Definite integral of a polynomial
% POLYDEFINT(p,a,b)returns the value I of the definite integral of poly-
% nomial p (in MATLABŪ polynomial form) over the real interval [a,b].
%
% See also polyint, polyder
%
% Detailed help, with examples, availa... |
%% GRID SEARCH FOR SVM. ORIGINAL IMBALANCED DATA
%% Dataset, exploratory data analysis and Method
%There are 6497 entries (before removal of missing values), 12 physiochemical wine quality predictors and
% 1 target value – the quality of the wine. Continues values would need
%to be normalized since there are som... |
clc;
clear;
% Зчитування зображень
X = imread('x2.bmp');
Y = imread('y2.bmp');
% Приведення елементів вхідних матриць до десяткових дробів
X = double(X);
Y = double(Y);
% Доповнення матриці Х рядком одиниць
X = [X; ones(1, size(X, 2))];
% Алгоритм за формулою Гревіля (початок)
% Перший крок
a = X(1, :).';
A(1, :) =... |
function [ r, idx ] = movingMin( ticks,len,type )
%MOVINMIN 移动求最小值
% @ luhuaibao
% 2014.6.3
% inputs:
% ticks, Ticks类
% len, 计算长度
% type, 供选择，包括'last','bid','ask'
if ~exist('type','var')
type = 'last';
end ;
switch type
case 'last'
[ r, idx ] = movMin0( ticks.last, len ) ;
... |
function DetectionResult=IntrusionDetectionCallback(context,action,CSIdata)
global PS;
Amplitude=GetAmplitude(1,1,15,CSIdata);
PreprocessData=ButterworthFilter(Amplitude,20,5,4,'low');
% 1. Get the silent environment threshold
if action == context.CALLBACK_INIT
PS.thres=GetVar(Preprocess);
% 2. Detect intrus... |
function psnr = PSNR_calculation(img1, img2)
[row, col] = size(img1);
psnr = sum(sum(((double(img2)-double(img1)).*(double(img2)-double(img1)))));
psnr = psnr/(row*col);
end |
function fAverageRMS = CalculateRMS_Music_7ch(InputFolder)
sInputFileCh0 = [InputFolder,'\ch0.wav'];
sInputFileCh1 = [InputFolder,'\ch1.wav'];
sInputFileCh2 = [InputFolder,'\ch2.wav'];
sInputFileCh3 = [InputFolder,'\ch3.wav'];
sInputFileCh4 = [InputFolder,'\ch4.wav'];
sInputFileCh5 = [InputFolder,'\ch5.wav'];
sInputFi... |
function eeg = button_preprocessing_training(eeg,nSecInterest,strOrder,unpressValue,verbose)
iChannel = eeg.map_ch('TRIG');
dataButton = eeg.data(iChannel,:);
% dataButton(dataButton < 0.5) = 2.99;
dataButton(dataButton < 0.5) = 1;
% dataButton(dataButton < 0.5) = ceil(unpressValue/2);
trigButton = find(dataBu... |
function perfect=createPopulation(dataLength,stim, populationSize)
t=1/256:1/256:(dataLength/256);
base(1,:)=(sin(2*pi*stim*t)+1)/2;
base(2,:)=(cos(2*pi*stim*t)+1)/2;
base(3,:)=(sin(4*pi*stim*t)+1)/2;
base(4,:)=(cos(4*pi*stim*t)+1)/2;
base=base';
for i=1:1:populationSize
perfect(:,i,:)=base;
end
|
%%
% For a Given Photocell,
% Given a Fixed Lux of illumination, Find the relation of Voltoge and
% Ampere.
%%
clear
clc
close all
dirpath='./figures';
if ~exist(dirpath,'dir')
mkdir(dirpath);
end
for i = [503 1003 1495 2000 2500 3000]
AnalyzeData(i)
end
function AnalyzeData(Lux)
sampling_resistor=100... |
function [out_values, cluster_nr] = contract_to_cluster_mean(in_values, tolerance, tolerance_mode);
% [out_values, cluster_nr] = contract_to_cluster_mean(in_values, tolerance, tolerance_mode);
%
% /!\ WARNING /!\ - THIS IS A DUMB ALGORITHM CREATED FOR A VERY SPECIFIC PURPOSE.
%
% TAKES A RANGE OF VALUES THAT SHOULD... |
%Hi Ta, would you mind mannually choose to execute some part of the code.
%I hope my explanation is clear. Thank you very much!
%problem a,b
%[h m Q] = EMG(0,'stadium.bmp',4);
%[h m Q] = EMG(0,'stadium.bmp',8);
%[h m Q] = EMG(0,'stadium.bmp',12);
%problem c
%[h m Q] = EMG(0,'goldy.bmp',7);
%below part invoke the bu... |
function [ROIImageInfoNew, ROIBWInfoNew, CDataSetInfoNew]=Resample_Wrapper(ROIImageInfo, ProgramPath, ROIImageInfoNew, CDataSetInfo, ROIBWInfo, ResampleImageFlag, ResampleROIFlag, BoxKernelFlag)
%Interpolate kernel
if nargin > 7
BoxKernelFlag=BoxKernelFlag;
else
BoxKernelFlag=0;
end
%--Resample Image... |
function [ J ] = basic_tutorial3_costFunctionJ( X, y, theta )
%UNTITLED 此处显示有关此函数的摘要
% 此处显示详细说明
m = size(X,1);
prediction = X*theta;
sqrErrors = (prediction-y).^2;
J = 1/(2*m) * sum(sqrErrors);
end
|
function images = enhanceContrastALS(images, num_row, num_col)
%linear stretching without user input
%automatically generate parameter m,c
%Iin: input image
%noise: number of noise pixels to be ignored
%define the first and last 10 pixels as noise
noise=10;
%retrieve each image
... |
n = 12;
xmax = 100; ymax = 200; xmin = -xmax; ymin=-ymax;
%xs = xmin + (xmax-xmin).*rand(n,1);
%ys = ymin + (ymax-ymin).*rand(n,1);
mu = [0 0]; %[1 2];
Sigma = 25*[1 .5; .5 2];
R = chol(Sigma);
R = [30 0; 0 60];
z = repmat(mu,n,1) + randn(n,2)*R;
ch = z(convhull(z),:);
figure(1); hold off
plot(z(:,1),z(:,2),'o','... |
function run_null_rf()
dsp2.cluster.init();
conf = dsp2.config.load();
epoch = 'targacq';
is_per_freq = true;
n_trees = 50;
if ( ~is_per_freq )
assert( numel(freq_rois) == numel(band_names) );
end
meas_type = 'coherence';
analysis_type = 'svm';
io = dsp2.io.get_dsp_h5();
base_p = dsp2.io.get_path( 'Measures', ... |
classdef MHyProSupportFunction < MHyProGeometricObject
methods (Access = public)
% Create a HyPro support function
function obj = MHyProSupportFunction(varargin)
obj.Type = 3;
if nargin == 0
% Call default constructor
ob... |
clear
load simdata
cameraSensor=zeros(nDetectors,1);
% cameraSensor=detectorCounts.detid
[a,~,c] = unique(detectorCounts.detid);
out = [a, accumarray(c,detectorCounts.ppath)];
out(:,1)=out(:,1)-1;
cameraSensor(out(:,1))=double(out(:,2));
cameraImage=reshape(cameraSensor,[ySize/detSize,xSize/detSize]);
figure,
image... |
% this script tests PL_GetWFEvs (get waveforms and events) function
% before using any of the PL_XXX functions
% you need to call PL_InitClient ONCE
% and use the value returned by PL_InitClient
% in all PL_XXX calls
s = PL_InitClient(0);
if s == 0
return
end
% call PL_GetWFEvs 10 times and plot the wav... |
function demo_function(StartTime,EndTime,GPU_Mode, Parallel_Mode,Number_of_Cores,Action_Strategy_List,varargin)
% Add all necessary libraries
addpath(genpath('/home/hoa/Dropbox/Apps/Matlab/Utilities'));
try
addpath(genpath('/fast/users/a1708618/Dropbox/Apps/Matlab/Utilities'));
catch
disp... |
clear all
close all
% make X number of uncorrelated channels
nr_antennas = 2:2:8; % dont use more than 8, error on plotting due to color function.
nr_realizations = 1000;
SNR=316.23;
for o = 1:length(nr_antennas);
H=zeros(nr_antennas(o),nr_antennas(o),nr_realizations);
for r=1:nr_realizations
... |
%CREATE TEMPLATES
%Letter
Alif=imread('bitmap_huruf\alif.bmp');Ba=imread('bitmap_huruf\ba.bmp');
Ta=imread('bitmap_huruf\ta.bmp');Tsa=imread('bitmap_huruf\tsa.bmp');
Jim=imread('bitmap_huruf\jim.bmp');Ha=imread('bitmap_huruf\ha.bmp');
Kha=imread('bitmap_huruf\kha.bmp');Dal=imread('bitmap_huruf\dal.bmp');
Dzal=imread('b... |
% ======================================
% Cycle-slip detection in measurement domain
%
% zhen.dai@dlr.de
%
% last modified: 2011.Oct
% ======================================
% display the standard deviation of differenced carrier phase data
% with/without the current carrier phase measuremen
function GUI_Results_Disp... |
function varargout = gui2(varargin)
% GUI2 MATLAB code for gui2.fig
% GUI2, by itself, creates a new GUI2 or raises the existing
% singleton*.
%
% H = GUI2 returns the handle to a new GUI2 or the handle to
% the existing singleton*.
%
% GUI2('CALLBACK',hObject,eventData,handles,...) calls the l... |
clear all
close all
clc
format long
format compact
% parameters
Physicsparams = setPhysicsParams(); % physics parameters
MPIparams = setMPIParams(Physicsparams, [0 0 3]); % MPI machine parameters
fileID = fopen('last_data_no_correction.txt');
C = textscan(fileID,'%f %f %f %f %f %f %*[^\n]', 'Delimiter', ... |
classdef filterCpsearn < handle
% Determines how individuals are filtered out
%{
%}
properties
% Drop people in group quarters?
dropGq
dropZeroEarn
dropNonWageWorkers
% cS.male, cS.female
sex
% cS.raceWhite, ...
race
% Age in PREVIOUS year (where earnings observed)
ageMin
ageMax
... |
%% an example to demonstrate PAW phase reconstruction
%% load physical system parameters
systemParameters = struct(...
'wavelength',0.56e-6, ... % wavelength in meter
'totalMagnification',10, ... % Total Magnification
'NAi', 0.3, ... % illumination NA
'NAd', 1.0, ... ... |
function [oe, r, v, jd] = planet_oe_and_sv ...
(planet_id, year, month, day, hour, minute, second)
% This function computes the orbital elements, the state vector, the velocity
% and the julien day for a planet.
% Based on Algorithm 8.1 from Orbital mechanics for engineering students,
% 2010, by H.D. Curtis
%... |
function a = setState_SP(a,sp)
% SETSTATE_SP Set the specific entropy [J/kg/K] and pressure [Pa].
%
% setState_SP(a, sp) sets the specific entropy and pressure
% of object a, holding its composition fixed. Argument 'sp' must
% be a vector of length 2 containing the desired values for the specific
% ent... |
function [Valigned,TMatrix,Vsource,Hsource,Rsource,Vtarget,Htarget,Rtarget] = alignDatasets(Vsource,Hsource,Vtarget,Htarget,interpmethod, OutputView)
if nargin<5
interpmethod = 'nearest';
end
[TMatrix,Vsource,Hsource,Rsource,Vtarget,Htarget,Rtarget] = ...
MakeTransMatrix(Vsource,Hsource... |
function [t,g] = Gaussian_pulse(M,K,a)
t = linspace(-M/2, M/2, M*K+1);
t = t(1:end-1);
t = t';
% Equality must hold: a = (1/(B*Ts))*sqrt(ln(2)/2)
g = (sqrt(pi)/a)*exp(-(pi^2)*(t.^2)/(a^2));
g = g / sqrt(sum(g.*g));
|
function z = linear_conv(x, y)
%debug
% x = [5 1 -2 4];
% y = [1 2 3];
%end debug
N = length(x)+length(y)-1;
xpad = [x zeros(1,N-length(x))];
ypad = [y zeros(1,N-length(y))];
z = zeros(1, N);
for k=0:(N-1)
for n = 0:k
z(k+1) = z(k+1) + xpad(n+1) * ypad(k-n+1);
... |
speech_vector = audioread('speech.au');
X = double(speech_vector);
subplot(4,1,1)
Y2 = Uquant(X,2^7);
E = Y2 - X;
[c,lags] = xcorr(E,Y2,200,'unbiased');
plot(lags,c)
title('cross-correlation E = Y - X, Y = Uquant(sv,2^7)')
xlabel('lags')
ylabel('c')
subplot(4,1,2)
Y2 = Uquant(X,2^4);
E = Y2 - X;
[c,lags] = xcorr(E,Y2,... |
h = 900;
min_y = 120;
max_y = 480;
min_x = 70;
max_x = 330;
% Threshold values
min_thresh = 30;
max_thresh = 500;
% Get image from depth sensor
%depth = getsnapshot(depthVid);
%color = getsnapshot(colorVid);
color = imread('doos_leeg_overlap_RGB.png');
load('depth_lege_doos.mat');
raw_matrix = depth;
%Run the sob... |
clear;
load X_train.mat;
load X_test.mat;
tic;
n= nnz(X_test);
Tnum = n;
RMSE=0.0;
[x,y,v]=find(X_test);
for i=1:1:Tnum
weight=0.0;
score=0.0;
Tsim = sim(:,x(i));
Ttrain = train(:,y(i));
for j = 1:1:10000
% if temp_train(j) > 0.5
score = score + Tsim(j)*Ttrain(j);
... |
% Calculate baseline LFP power for single data file
% compare first 5min and last min spectra
% First 5min
dmat = detrend(First5m.(chan_names{ch}))';
[C_First5ms,ph,s12,S_First5ms,S_First5ms,t,f]=cohgramc(dmat,dmat,movingwin,params);
% NOTE I just use cohgram here because it has a moving window option. This
%... |
%% 8-15-2016 - script to compare response times once they've been calculated
% make sure you have vectors buttonLocsVecCort, buttonTactDiff,
% tactorLocsVecTact
% set bounds on data, assume rxn time has to be greater than 200 ms and
% less than 1 s
current_direc = pwd;
%save(fullfile(current_direc, [sid '_compare... |
% function RESULTS = assessment(Labels,PreLabels,par)
% function [ConfusionMatrix,Kappa,OA,varKappa,Z, CI] = assessment(Labels,PreLabels,par)
function RESULTS = assessment( Labels, PreLabels )
%
% function RESULTS = assessment(Labels,PreLabels,par)
%
% INPUTS:
%
% Labels : A vector containing the true (a... |
% SPTK commands
X2X = '/Users/sivanandachanta/tts_tools/SPTK_3.6/bin/x2x';
MGCEP = '/Users/sivanandachanta/tts_tools/SPTK_3.6/bin/mcep';
LPC2LSP = '/Users/sivanandachanta/tts_tools/SPTK_3.6/bin/lpc2lsp';
AVERAGE = '/Users/sivanandachanta/tts_tools/SPTK_3.6/bin/average';
NAN = '/Users/sivanandachanta/tts_tools... |
function [out, X, distances] = get45Marginal(in, steps)
if nargin<2
steps = 50;
end
[lenA, lenB] = size(in);
B = repmat( (1:lenA)',[1 lenB]);
A = repmat( (1:lenB) ,[lenA 1]);
distances = sqrt(A.^2+B.^2).*sin( atan(B./A) - pi/4);
minD = min(distances(:));
maxD = max(distances(:));
stepSize = (maxD-minD)./(steps-... |
function binary=en_coef2D_new(coef,H0,W0,delta,binary)
%N=int16(size(coef)); H0=bitshift(N(1),-3); W0=bitshift(N(2),-3);
%binary=SFcode(H0,1536); binary=[binary SFcode(W0,1536)];
Nsub=bitshift(int32(numel(coef)),-2);
if Nsub<=bitshift(int32(2),18)
binary=en_coef2D_new_sub1(coef,delta,H0,W0,binary);
elseif Nsub<=... |
function y = calcMSE(im1, im2)
[height width cdim] = size(im1);
y = sum((im1(:)-im2(:)).^2)/(height*width*cdim);
end
|
function H = simplex_continuity(tri, spline_poly_order, spline_cont_order,...
c_OLS_coeff)
% SIMPLEX_CONTINUITY Creates the continuity matrix H
%
% Inputs:
% - tri: MATLAB triangulation object
% - spline_poly_order: order of the polynomial spline
% - spline_cont_order: order to which the splines have to be cont... |
function [out1, out2] = gp_sod(logtheta, covfunc, likfunc, x, varargin)
% gpr_sod - Gaussian Process regression, using the Subset of Data
% approximation.
%
% usage: [loghyper sod] = gpr_sod(logtheta, covfunc, likfunc, x, y, N, method,splitLen, 'split')
% or: [mu S2] = gpr_sod(logtheta, covfunc, likfunc, x, y, N... |
function [na1,na2]=coocur_repeat(a1,a2)
if length(unique(a1))~=length(a2) %Means a1 contains repeated values
[na1,f2]=unique(a1);
na2=[];
for j=1:length(na1)
[~,f2]=min(abs(a2-na1(j)));
na2=[na2 a2(f2)];
end
end
if length(unique(a2))~=length(a1)%Means a2 contains repeated values
[n... |
% %% INIT
%
% clear all;
% close all;
% clc
% imaqreset
%
% % Data Aquisition
% colorDevice = imaq.VideoDevice('kinect',1);
% depthDevice = imaq.VideoDevice('kinect',2);
%
% colorImage = step(colorDevice);
% depthImage = step(depthDevice);
% ptCloud = pcfromkinect(depthDevice,depthImage,colorImage);
% ... |
%% MASCRET Quentin - Copyright 2017 %%
% This function is based on an analysis. First of all, I saw that during
% stray time, attack of Wang & Al. 2011 algorithm parameter will be short
% less than 4 windows over my adaptive threshold. Moreover, peak are
% numerous and by the way have a short attack. My idea is to crea... |
load('../data/k_fold_partitions_noisy_data.mat');
% Best choosen parameters for 'traingda'
BEST_NEURON_L1 = 15;
BEST_NEURON_L2 = 0;
BEST_LR_INC = 1.1;
BEST_LR_DEC = 0.5;
BEST_LEARNING_FUNCTION = 'traingda';
BEST_MC = -1;
BEST_LR = -1;
%VARIABLE number of epoch
MAX_EPOCH = 1000;
% set of integer versions of our label... |
function [T10_Data, T10_Info, T10_desc] = compute_T10_map_from_PDW_data(PDW_Struct, DCE_Struct, ROIs_by_slice, T10_estimation_type, T10_correction_struct, init_T10_Data)
T10_Info = []; T10_desc = [];
MR_volume_size = size(PDW_Struct.Data{1});
[flip_angles, TRs, TEs] = extract_MR_params_for_VFA_estimation(PDW_Struct... |
%% Load Fundamental Spectrum (own measurement)
% filename_sp='U:\Measurement_Data\OAC_IFROG\2019_05_02_ACER\venteon_spectrum_CEP_stabil.txt';
filename_sp='Z:\People\S.Peter\projects\IFROG\Venteon_with_APE_wavescan_noheader.txt';
comma2dot(filename_sp);
venteon_spectrum=load([filename_sp(1:end-4) '_dot.txt']);
wl0=... |
G=JPsv;
members=properties(G);
classes1={{12};{20}};
classes2={{12};{21}};
classes3={{12};{22}};
for i=1:numel(members)
% G.(members{i}).default.train_classifier('name','c1220','classes',classes1,'blocks_in',1:10,'channels',1:64,'time',1:64);
% G.(members{i}).default.train_classifier('name','c1221','classes'... |
function [type_map,quality_map,maxquality_map] = generate_maps(Prop)
% Generates a map from a png file.
% creates a 1000x1000 map with 0:4 values, 4:1 for rbgk and 0 for
% anything else.
% When drawing in GIMP, choose for H value:
% 330-360 and 0-30: Nothing MEAN: 0
% 30-90: Flower 1 MEAN: 60
%... |
function [signalMovie] = createSignalBasedMovie(inputSignals,inputImages,varargin)
% uses images and signals for sources from an original movie to create a cleaner, more binary movie
% biafra ahanonu
% started: 2014.07.20 [14:09:34]
% inputs
% inputSignals - [n t], n = number of signals, t = time
% inputImages ... |
% fprintf('cell=%d\n', cell); 这个打印时间开销巨大
xcell = ceil(cell / Order); ycell = mod(cell - 1, Order) + 1;
goto_nextcell = 0;
cell_record(cell_record_ptr) = cell;
cell_record_ptr = cell_record_ptr + 1;
while((goto_nextcell == 0) && (ptrs(cell) <= Order))
if cur_mark(xcell, ycell, ptrs(cell)) == 0
ptrs(ce... |
function value = statistic(varargin)
value = feval(varargin{:});
function result = epoch_offset()
result = 'extract(epoch from time)';
function result = byte_offset(field)
sp = StatPacket;
size = eval(['sp.size_' field]);
if (size == 1)
result = num2str(eval(['sp.offset_' field]));
result = ['(b' result ')'];
el... |
%% Try different analyses and develop ISETBIO with the Vernier methods.
scene = sceneCreate('vernier');
oi = oiCreate;
cm = coneMosaic;
locationThetaDegrees = 90;
locationRadius = 10;
|
clc
clear all
C1 = 5;
C2 = 3;
n = 100;
D = 100;
dx= 0.5;
dt=0.001;
R = 8.314;
T = 400;
a=3*10^-5
%for down-hill diffusion O < 2RT
arr_conc = zeros(100);
arr_conc_old = zeros(100);
%loop to find the initial array concentration
for i = 1:100
for j = 1:100
%creating a 3d array with ran... |
function UpdateTexture( im, isOrg)
%UPDATETEXTURE Summary of this function goes here
% Detailed explanation goes here
global imageData
im = imageConvertNorm(im,'uint8',true);
if (~exist('isOrg','var') || isempty(isOrg) || true==isOrg)
lever_3d('loadTexture',im,imageData.PixelPhysicalSize);
else
lever_3d('lo... |
function hetero_MM(cs,cb,sav_fname,T,t,Imic, ksmm, kb,km, Y, nx, ny, options)
d2dec_dcs2= @(csm,cbm,ksmmf,kmf)(-(2.*cbm.*kmf.*ksmmf)./(csm+ kmf).^3);
d2dec_dkm2= @(csm,cbm,ksmmf,kmf) (2*cbm*csm*ksmmf)./(csm + kmf).^3;
d2dec_dkmdksmm= @(csm,cbm,ksmmf,kmf) -(cbm*csm)./(csm + kmf).^2;
d2dec_dcsdcb= @(csm,cbm,ksmmf,kmf)(k... |
%M=4;
%Nt=4;
%Nr=4;
%SNR_Vector=-15:1:15;
%BBB=ABER_ANA_QSM_Rayleigh_no_CSE(M,Nt,Nr,SNR_Vector)
%semilogy(SNR_Vector,BBB)
SNR_Vector=-10:1:15;
BBB=ABER_ANA_QSM_Rayleigh_no_CSE(4,4,4,SNR_Vector);
figure;
semilogy(SNR_Vector,BBB,'-*b') % QPSK/4TX/4RX
hold on
DDD=ABER_ANA_QSM_Rayleigh_no_CSE(4,8,4,SNR_Vecto... |
function [ ] = plot_ace_relationship_bygas_serialmonth( gas_in, years_in, do_plot )
%A funcion to plot the relationships between ace gases for a given year.
% *INPUT*
% gas_in: STRING - the name of the gas for which you want to
% compare the climatologies.
%
% filename_oldclim: STRING - t... |
function [X, XTest] = splitTrials(X, fold, nFolds)
% split X's trials into training dataset and testing dataset
% The dimensions of X are: nBins * nConds * nTrials * nCells
nTrials = size(X,3);
if nFolds == 1
XTest = [];
else
s = rng;
rng(0) % always split the same way
iTrials = mod(1:nTrials,nFolds)+1... |
fs = 16000;
source_test_file = {'VC_COSPRO_VAD\F002\COSPRO 03_F002phr723_d.wav'};
audio_file=source_test_file;
mccDIM = 39;
addpath('STRAIGHT\STRAIGHT\STRAIGHTV40_006b');
M = 2^15;
frame_length=25; % STRAIGHT analysis, synthesis set up. 25msec.
frame_shift=5; % STRAIGHT analysis, synthesis set up. 25msec.
prmP.de... |
function Beamforming_Rypkema
function [data, time, signal] = simulate_data(phones, sound_speed, noise_pwr, signal_pwr, sampling_rate, samples, signal_hz, signal_pulse, signal_azimuth, signal_elevation)
%%% simulate a 'pulse' at frequency 'signal_hz' for duration of
%%% 'signal_pulse', and occuring centered at ... |
function xs_hat = WavRecSep(xs_hat, xw_hat, h_hat, g_hat, decimation)
% x_hat = WavRecSep(xs_hat, xw_hat, h_hat, g_hat, decimation)
%
% Frequency-domain implementation of a separable wavelet reconstruction.
% In particular:
% - the input must be the DFTs of the wavelet coefficients in each subband;
% - the function ret... |
% Yuan Gao, Rice University
test_result = zeros(3,3);
BUDDHA_TEST = dir('/Users/gaoyuan/Documents/MATLAB/TestDataset_1');
BUTTERFLY_TEST = dir('/Users/gaoyuan/Documents/MATLAB/TestDataset_2');
AIRPLANES_TEST = dir('/Users/gaoyuan/Documents/MATLAB/TestDataset_3');
TRAINED_DATA = [FEAT.BUDDHA; FEAT.BUTTERFLY; FEAT.AIR... |
%Space2: the GUI for Space2 tests
% NO-LONGER uses dynamically updated buffers to allow longer stimuli (max about 30,000 msec)
% stimuli are NOT written to disk for each loc, then loaded and played out
% note: when changing stim duration, the next play-out has a large glitch
% to accomodate this, each run of the ... |
function[mu, var, time] = gprPITC(K, Ks, Kss, y, hyp)
tic
[n, ~] = size(K);
sigma = exp(2*hyp.lik);
% choose a random set of m_rank indices for the active set
perm = randperm(n);
u = perm(1:hyp.k);
m=length(u);
tic;
[L, L_partition] = getLambda(K,getQ(K,1:size(K,1),1:size(K,1),u),sigma,m);
Sigma = getS(K,L,u,L_part... |
% First run the top script to set up the ss model.
top;
%%
% We will now close the loop around the system, and use a PI controller
% with our velocity feedback to choose a setpoint.
% This model will use SIMULINK to create the feedback system. |
function y = overlap_save(x,h,lc)
% Length of x
lx = length(x);
% Length of impulse response
lh = length(h);
% Sample size equals length of h minus 1 plus chunk size
x_b_size = lh - 1 + lc;
% Size of convolved output of x_b and h equals length of h minus 1 plus
% x_b_size.
y_b_size ... |
clear; close all; clc;
addpath(genpath(('../third_party')));
modelsDir = '../3dmodels/';
%% Parameters
modelName = 'jerboa';
resolution = 120;
pad = 0;
%pad = floor( ((sqrt(3) - 1)/(2 * sqrt(3))) * resolution + 1);
%% Model initialization
modelPath = strcat(modelsDir, modelName, '.stl');
Original = dippingPreproce... |
function handles = sortLayers(handles)
%SORTLAYERS Sorterer T2* billederne i snit
% Finder først de unikke værdier i T2-billedernes SliceLocation. Således
% opdeles der i lag (T2.LayerNo).
% Gemmer antallet af lag i handles (NumbOfLayers)
% For hvert lag gemmes de tilhørende billeder i handles (Layers.Imag... |
function T = read_fs_files(path)
T = fileread(path);
T = regexp(T, '\n', 'split');
if isempty(T{end}),T(end)=[];end
header_lines=cellfun(@(A) strcmp(A(1),'#'),T);
T(header_lines)=[];
T = cellfun(@(A) strsplit(A),T,'UniformOutput',false);
end |
classdef GTM_Pi_Norm < GTM_Pi
%GTM_Pi_Norm Summary of this class goes here
% Detailed explanation goes here
methods
function obj = GTM_Pi_Norm(img,rf,smoother)
obj@GTM_Pi(img,rf,smoother);
end
end
end
|
function output = dM(ax, ang)
if (norm(ax) == 0 | ang == 0 )
output = eye(3);
else
ax = ax/norm(ax);
output(1,1) = ax(1)^2+(ax(2)^2 + ax(3)^2)*cos(ang);
output(1,2) = -(ax(3)*sin(ang)) + ax(1)*ax(2)*(1 - cos(ang));
output(1,3) = ax(2)*sin(ang)+ax(1)*ax(3)*(1 - ... |
function metrics = calculateMetrics(pattern)
% This function calculates a set of metrics for a provided pattern. Any
% set of functions can be called from here, that each generate their own
% metric(s) for a pattern, and then these are combined into a single row
% vector that is visible to the remainder of the cod... |
classdef TPA_MotionCorrectionManager
% TPA_MotionCorrectionManager - corrects image motion in image stack using
% different algorithm
% Inputs:
% none
% Outputs:
% motion path
%-----------------------------
% Ver Date Who Descr
%-----------------------------
% ... |
function Shrew_Decoding
%%
SaveDir = [ cd '\' 'Randomized' '_Decode\'];
if exist( [SaveDir 'MD'] ) ~= 0
rmdir([SaveDir 'MD'],'s')
mkdir([SaveDir 'MD']);
elseif exist( [SaveDir 'MD'] ) == 0
mkdir([SaveDir 'MD']);
end
if exist( [SaveDir 'PFC'] ) ~= 0
rmdir([SaveDir 'PFC'],'s')
... |
clc; clear; close all;
load('T0020_points.mat');
thetaH = pi/2;
thetaPrim = thetaH - theta ;
phiPrim = atan((z./y).*cos(thetaPrim));
Err = abs(phi - phiPrim);
imagesc(Err);figure(gcf); |
function im_all = spiral3drecon_200520(doRots, Ndel, doGoldenAngle, doTraj)
% function im_all = spiral3drecon_200520(doRots, Ndel, doGoldenAngle, doTraj)
%
% spiral3drecon
%
% Luis Hernandez-Garcia @UM 2020
%
% 1- This script reads FIDs from the GE scanner acquired with a
% noncartesian 3d trajectory
% 2 - it reads the... |
function Capacityreconfskv3 = Capacity_SMTreconfskv3(Nr,SNR_Vector,freqno,reconantenna)
Capacityreconfskv3=Nr*log2(1+10.^(SNR_Vector/10))+log2(freqno)+log2(reconantenna);
end |
function varargout=sml1_imana_BG_new(what,varargin)
% ------------------------- Directories -----------------------------------
%baseDir ='/Users/eberlot/Documents/Data/SuperMotorLearning';
baseDir ='/Volumes/MotorControl/data/SuperMotorLearning';
behavDir =[baseDir '/behavioral_data/data'];
... |
function p = predict(theta, X)
%PREDICT Predict whether the label is 0 or 1 using learned logistic
%regression parameters theta
% p = PREDICT(theta, X) computes the predictions for X using a
% threshold at 0.5 (i.e., if sigmoid(theta'*x) >= 0.5, predict 1)
m = size(X, 1); % Number of training examples
% You nee... |
function [C, sigma] = dataset3Params(X, y, Xval, yval)
%EX6PARAMS returns your choice of C and sigma for Part 3 of the exercise
%where you select the optimal (C, sigma) learning parameters to use for SVM
%with RBF kernel
% [C, sigma] = EX6PARAMS(X, y, Xval, yval) returns your choice of C and
% sigma. You should co... |
function ans = equation_11( J, mu )
ans=J+mu+1;
end |
function [positions] = modalities_sample(modalities, mask, N, kernel)
if isempty(modalities.map)
positions = [];
return;
end
modalities.map = scalemax(modalities.map, 1);
mask = mask .* (imfilter(double(modalities.map > 0.2), ones(5)) > 15);
positions = zeros(N, 2);
... |
r = {};
% r1 = load('comparacao2.mat');
% r1 = r1.resp;
% r = [r,r1];
% r1 = load('comparacao3.mat');
% r1 = r1.resp2;
% r = [r,r1];
% r2 = load('comparacao4.mat');
% r2 = r2.resp;
% r = [r,r2];
r3 = load('fieldmap_analysis_modelo5_6segmentos.mat');
r3 = r3.r;
r = [r,r3];
r4 = load('fieldmap_analysis_modelo6_6segment... |
function [MatrixResults, time_MTF_GLP_CBD, I_MTF_GLP_CBD] = doMTF_GLP_CBDSens0(imageDataFile)
% doMTF_GLP_CBDSens0 performes a MTF_GLP_HPM reconstruction of a Multi-spectral image,
% whose relevant information is contained in ./Sensors/data/imageDataFile.mat file,
% the obtained results are compared with groundtruth fo... |
function assetList = FetchAssetList( index_name, index_time,conn, table_name )
%FETCHASSET 通过查询条件取股票代码
% conn 连接数据库句柄
% table_name 表名
% index_name 给定的指数
% index_time 给定的时间
% Cheng,Gang; 2013
%% default values
if nargin <4
table_name = '[as].aindexmembers_temp';
if nargin < 3
conn = database('db','sa',... |
classdef TrialTonesInstruction < WBTrial
methods
function start(this)
roundn = this.flow.variable(['Block0-RoundNum']);
% CREATE THE INSTRUCTION SCREEN
ti = WBTextDisplay('TONES TEXT', '', 26);
%ti.xLoc = 50;
if (roundn == 0)
... |
function op_setfigcolorbar(ax,ylabel_str,pos)
if nargin > 1
gca = ax;
end
set(ax,'fontsize',20,'linewidth',1.5,'box','on')
hylabel = ylabel(ax,ylabel_str,'rotation',270);
h_ylabel = get(ax,'Ylabel');
h_xlabel = get(ax,'Xlabel');
set(h_ylabel,'Fontsize',20)
set(h_xlabel,'Fontsize',20)
set(gcf,'color',[1 1 1])
pos = ... |
function [ x, y ] = XYZ2xy( X, Y, Z )
%
x = X/(X + Y + Z);
y = Y/(X + Y + Z);
end |
% Sean Smith and Tommy Unger
% CS 542 Spring 2016
% Spring 2016
%Markov random field
close all
%im = img_to_bip('images/bayes_dirty.png');
im = imread('images/bayes_dirty.png');
im = int8(im);
im = (im * 2) - 1;
y = im;
sz = size(im);
xdim = sz(2);
ydim = sz(1);
count = 0;
wrapN = @(x, N) (1 + mod(x-1, N));
h = ... |
function R = resilient_estimation_Withoutprior(m,n,Pa)
% function R = resilient_estimation_Withoutprior(m,n,Pa)
% Description:
% This function is evaluate the performance of resilient
% estimation, if estimate error is larger than 1%*x0, the
% estimation fails, otherwise it succ... |
% GLUECK: Growth pattern Learning for Unsupervised Extraction of Cancer Kinetics
% Akaike Information Criterion, AIC
% as from [Burnham and Anderson, 2003]
function aic = model_aic(alfa, sigma, p, M, y)
N = length(M);
sum_sse = model_sse(alfa, sigma, M, y);
aic = N * log(sum_sse / N) + 2*p;
end |
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