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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | epfl-lasa/ML_toolbox-master | SB1_ExampleRegress.m | .m | ML_toolbox-master/methods/toolboxes/rvmbox/SB1_ExampleRegress.m | 2,960 | utf_8 | dff444c7452808b3e444f5642c4592c6 | % SB1_EXAMPLEREGRESS Example of Sparse Bayes Regression
%
% SB1_EXAMPLEREGRESS(N,NOISE,KERNEL,WIDTH,MAXITS)
%
% INPUT ARGUMENTS:
%
% N Number of training points
% NOISE Noise standard deviation to be added
% KERNEL Kernel function to use (see SB1_KERNELFUNCTION)
% WIDTH Ker... |
github | epfl-lasa/ML_toolbox-master | getEnvironment.m | .m | ML_toolbox-master/methods/toolboxes/rvmbox/getEnvironment.m | 390 | utf_8 | 581e424b3e8c67ea9dd9e885bd2aed0c | % GETENVIRONMENT Read value of "global" variable
%
%
% Copyright 2009 :: Michael E. Tipping
%
% This file is part of the SPARSEBAYES baseline implementation (V1.10)
%
% Contact the author: m a i l [at] m i k e t i p p i n g . c o m
%
function value = getEnvironment(variable)
VA = get(0,'UserData');
if isfi... |
github | epfl-lasa/ML_toolbox-master | SB1_RVM.m | .m | ML_toolbox-master/methods/toolboxes/rvmbox/SB1_RVM.m | 2,769 | utf_8 | af5e3d63fd9a4a9decbda38805265c6b | % SB1_RVM Kernel specialisation of sparse Bayes model (RVM)
%
% [WEIGHTS, USED, BIAS, ML, ALPHA, BETA, GAMMA] = ...
% SB1_RVM(X,T,ALPHA,BETA,KERNEL,LEN,USEBIAS,MAXITS,MONITS)
%
% OUTPUT ARGUMENTS:
%
% WEIGHTS Parameter values of estimated model (sparse)
% USED Index vector of "relevant" ... |
github | epfl-lasa/ML_toolbox-master | car_run_policy_episode.m | .m | ML_toolbox-master/methods/reinforcement_learning/rl_common_functions/car_run_policy_episode.m | 2,216 | utf_8 | 306525e1b92cb4c139f3c82718ebb5dc | function [total_reward,steps,xurxp,f,num_actions_taken] = car_run_policy_episode(maxsteps,policy,reward,Hz,grafic,start_type,bRecord)
%RUN_EPISODE
%
%
% input ----------------------------------------------------
%
% o max_step: (1 x 1), maximum number of steps for the episode
%
% o lambda: (1 x 1), TD... |
github | epfl-lasa/ML_toolbox-master | bellman_residual.m | .m | ML_toolbox-master/methods/reinforcement_learning/rl_common_functions/bellman_residual.m | 936 | utf_8 | f6a3a2a78aa83b22b9749c445852e4fe | function [ res ] = bellman_residual(Qt,Qtmp)
%BELLMAN_RESIDUAL Computes the Bellman residual
%
% input -------------------------------------------------------
%
% o Q: Q-value function at time t
%
% o Qtmp: Q-value function at time t-1
%
vt = compute_value_function(Qt);
vtmp = compute_v... |
github | epfl-lasa/ML_toolbox-master | State_Initialise.m | .m | ML_toolbox-master/methods/reinforcement_learning/rl_common_functions/State_Initialise.m | 574 | utf_8 | 7c592c2ab0cc85fd664eca72fabd5e63 | function [ x ] = State_Initialise( start_type )
%STATE_INITIALISE Summary of this function goes here
% Detailed explanation goes here
if strcmp(start_type,'random') == true
x = init_state([-1,0.4],[-0.07,0.07]); %[x,xp]'
elseif strcmp(start_type,'semi-random') == true
x = init_state([-1,0],[-0.007,0.007]... |
github | epfl-lasa/ML_toolbox-master | compute_bellman_residual.m | .m | ML_toolbox-master/methods/reinforcement_learning/rl_common_functions/compute_bellman_residual.m | 990 | utf_8 | a9c9301b770cf346d02af02aeeaf2354 | function [ res ] = compute_bellman_residual(fqi_option)
%COMPUTE_BELLMAN_RESIDUAL Summary of this function goes here
% Detailed explanation goes here
nfq_Qk1 = initialise_nfq('split',2);
nfq_Qk2 = initialise_nfq('split',2);
N = size(fqi_option.qs,1);
res = zeros(N-1,1);
for k=2:N
nfq_Qk1 = get_Q... |
github | epfl-lasa/ML_toolbox-master | Episode_discrete.m | .m | ML_toolbox-master/methods/reinforcement_learning/mountain_car_functions/Episode_discrete.m | 2,310 | utf_8 | e7642c8f10e43121fa2394b78ad5eb55 | function [ total_reward,steps,Q,x_init] = Episode_discrete( maxsteps, Q , alpha, gamma,epsilon,statelist,actionlist,grafic,start_type)
%MountainCarEpisode do one episode of the mountain car with sarsa learning
% maxstepts: the maximum number of steps per episode
% Q: the current QTable
% alpha: the current learning rat... |
github | epfl-lasa/ML_toolbox-master | Episode_no_learning.m | .m | ML_toolbox-master/methods/reinforcement_learning/kNN-TD-MountainCar/kNN_me/Episode_no_learning.m | 2,155 | utf_8 | 353fa735a54ce65fbd68166088cd09ad | function [ total_reward,steps,xurxp] = Episode_no_learning( maxsteps, Q,reward,statelist,actionlist,k,grafic,start_type,bRecord)
%MountainCarEpisode do one episode of the mountain car with sarsa learning
% maxstepts: the maximum number of steps per episode
% Q: the current QTable
% alpha: the current learning rate
% ga... |
github | epfl-lasa/ML_toolbox-master | rl_demo_gui.m | .m | ML_toolbox-master/methods/reinforcement_learning/rl_gui/rl_demo_gui.m | 16,928 | utf_8 | 9f140a782fbb5a0f93974a1a2354f140 | function varargout = rl_demo_gui(varargin)
% RL_DEMO_GUI MATLAB code for rl_demo_gui.fig
% RL_DEMO_GUI, by itself, creates a new RL_DEMO_GUI or raises the existing
% singleton*.
%
% H = RL_DEMO_GUI returns the handle to a new RL_DEMO_GUI or the handle to
% the existing singleton*.
%
% RL_DEMO_G... |
github | epfl-lasa/ML_toolbox-master | Episode.m | .m | ML_toolbox-master/methods/reinforcement_learning/MoutainCar/Episode.m | 2,549 | utf_8 | 72f6f9ddf379e0c816eba032fb7366ed | function [ total_reward,steps,Q,x_init,us,xs,xurxp] = Episode( maxsteps, Q , alpha, gamma,epsilon,statelist,actionlist,grafic,bRecord)
%MountainCarEpisode do one episode of the mountain car with sarsa learning
% maxstepts: the maximum number of steps per episode
% Q: the current QTable
% alpha: the current learning rat... |
github | MaxChu719/HumanPoseEstimation-master | initialize_maxnet.m | .m | HumanPoseEstimation-master/initialize_maxnet.m | 4,261 | utf_8 | f15e44068f53953d1786f8c2e57622c3 | function net = initialize_maxnet()
net.meta.normalization.imageSize = [128, 128, 3] ;
net.meta.networkType = 'simplenn';
net.layers = { } ;
id = 0;
net = add_block(net, id, 5, 5, 3, 32, 2, 2) ; id = id + 1;
net.layers{end+1} = struct('type', 'pool', 'name', sprintf('poogmal%d', id), ...
'm... |
github | MaxChu719/HumanPoseEstimation-master | maxnet_deploy.m | .m | HumanPoseEstimation-master/maxnet_deploy.m | 6,420 | utf_8 | 4de7bfb0a6302a46a2cd9db592504bc9 | function net = maxnet_deploy(net)
%CNN_IMAGENET_DEPLOY Deploy a CNN
isDag = isa(net, 'dagnn.DagNN') ;
if isDag
dagRemoveLayersOfType(net, 'dagnn.Loss') ;
dagRemoveLayersOfType(net, 'dagnn.DropOut') ;
else
net = simpleRemoveLayersOfType(net, 'custom') ;
net = simpleRemoveLayersOfType(net, 'dropout') ;
end
if ... |
github | MaxChu719/HumanPoseEstimation-master | initialize_alexnet.m | .m | HumanPoseEstimation-master/initialize_alexnet.m | 3,416 | utf_8 | e2ad54c064fcd01143d11c35eade95e6 | function net = initialize_alexnet()
net.meta.normalization.imageSize = [224, 224, 3] ;
net.meta.networkType = 'simplenn';
net.layers = { } ;
id = 0;
id = id + 1;
net = add_block(net, id, 11, 11, 3, 96, 4, 0) ;
%net.layers{end+1} = struct(...
% 'name', sprintf('norm%d', id), ...
% 'type', 'normalize', ...
% ... |
github | bbasso/Research-master | untitled1.m | .m | Research-master/common/untitled1.m | 7,365 | utf_8 | 1175cc85fc2770fb39675446a2aacb6f | function varargout = untitled1(varargin)
% UNTITLED1 M-file for untitled1.fig
% UNTITLED1, by itself, creates a new UNTITLED1 or raises the existing
% singleton*.
%
% H = UNTITLED1 returns the handle to a new UNTITLED1 or the handle to
% the existing singleton*.
%
% UNTITLED1('CALLBACK',hObject... |
github | bbasso/Research-master | policy_play.m | .m | Research-master/common/policy_play.m | 10,075 | utf_8 | 552f7b311e90a3074abdfc7da84d5594 | function varargout = policy_play(varargin)
% POLICY_PLAY M-file for policy_play.fig
% POLICY_PLAY, by itself, creates a new POLICY_PLAY or raises the existing
% singleton*.
%
% H = POLICY_PLAY returns the handle to a new POLICY_PLAY or the handle to
% the existing singleton*.
%
% POLICY_PLAY('C... |
github | thomasantony/coursera-robotics-flight-master | QuadPlot.m | .m | coursera-robotics-flight-master/Week1/GainTuningExercise/QuadPlot.m | 5,212 | utf_8 | 9b869b07631faa5214a3a9c6cfae2cac | classdef QuadPlot < handle
%QUADPLOT Visualization class for quad
properties (SetAccess = public)
k = 0;
qn; % quad number
time = 0; % time
state; % state
rot; % rotation matrix body to world
color; % color of quad
... |
github | thomasantony/coursera-robotics-flight-master | QuadPlot.m | .m | coursera-robotics-flight-master/Week1/StoppingDistanceExercise/QuadPlot.m | 5,220 | utf_8 | 1f4b7d11af220cf6f1d5e395f4a180f9 | classdef QuadPlot < handle
%QUADPLOT Visualization class for quad
properties (SetAccess = public)
k = 0;
qn; % quad number
time = 0; % time
state; % state
rot; % rotation matrix body to world
color; % color of quad
... |
github | thomasantony/coursera-robotics-flight-master | QuadPlot.m | .m | coursera-robotics-flight-master/Week1/ThrustWeightExercise/QuadPlot.m | 5,220 | utf_8 | 1f4b7d11af220cf6f1d5e395f4a180f9 | classdef QuadPlot < handle
%QUADPLOT Visualization class for quad
properties (SetAccess = public)
k = 0;
qn; % quad number
time = 0; % time
state; % state
rot; % rotation matrix body to world
color; % color of quad
... |
github | thomasantony/coursera-robotics-flight-master | QuadPlot.m | .m | coursera-robotics-flight-master/Week1/GainTuningQuiz/QuadPlot.m | 5,220 | utf_8 | 1f4b7d11af220cf6f1d5e395f4a180f9 | classdef QuadPlot < handle
%QUADPLOT Visualization class for quad
properties (SetAccess = public)
k = 0;
qn; % quad number
time = 0; % time
state; % state
rot; % rotation matrix body to world
color; % color of quad
... |
github | ecobost/brain2sent-master | spm_get_bf.m | .m | brain2sent-master/code/Wu_deconv/spm_get_bf.m | 5,916 | utf_8 | ae9397cfc5136cfaec7a8cd5f37e05eb | function [xBF] = spm_get_bf(xBF)
% Fill in basis function structure
% FORMAT [xBF] = spm_get_bf(xBF)
%
% xBF.dt - time bin length {seconds}
% xBF.name - description of basis functions specified
% 'hrf'
% 'hrf (with time derivative)'
% 'hrf (with time and dispersion deri... |
github | ZHANGXinxinPKU/motion-deblurring-master | deconvtvl2.m | .m | motion-deblurring-master/code/code/deconvtvl2.m | 6,403 | utf_8 | 217f733df269e458bcfcea143f50d64f | function out = deconvtvl2(g, H, mu, opts)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% out = deconvtv(g, H, mu, opts)
% deconvolves image g by solving the following TV minimization problem
%
% min (mu/2) || Hf - g ||^2 + ||f||_TV
%
% where ||f||_TV = sqrt( a||Dxf||^2 + b||Dyf||^2 c||Dtf||^2),
% Dxf = f(x+1,y, t) - f(x,y,t... |
github | ZHANGXinxinPKU/motion-deblurring-master | structure_adaptive_map.m | .m | motion-deblurring-master/code/code/structure_adaptive_map.m | 1,986 | utf_8 | 66ec121d73919ec55080bfa327fcf37f | function [structure] = structure_adaptive_map(im, theta, nIters)
% Decompose the input IMAGE into structure and texture parts using the
% Rudin-Osher-Fatemi method. The final output is a linear combination
% of the decomposed texture and the structure parts.
%
% According to Wedel etal "An Improved Algorithm for TV-L1... |
github | ZHANGXinxinPKU/motion-deblurring-master | gradient_confidence_full.m | .m | motion-deblurring-master/code/code/gradient_confidence_full.m | 1,495 | utf_8 | cb4e415b9e2d7495b9da7dacd11f7dcf | function r = gradient_confidence_full(B,d)
%% Compate rmap
% Reference:
% Li Xu, Jiaya Jia,
% Two-Phase Kernel Estimation for Robust Motion Deblurring, ECCV 2010.
if (size(B,3) ==3)
B0 = rgb2gray(B);
else
B0 = B;
end
border = (d-1)/2;
B0 = double(B0);
y_padded = padarray(B0, [border border], 'symmetric', '... |
github | ZHANGXinxinPKU/motion-deblurring-master | deconvtvl1.m | .m | motion-deblurring-master/code/code/deconvtvl1.m | 6,551 | utf_8 | 4edd96e4d2a766f65612a717b003a24e | function out = deconvtvl1(g, H, mu, opts)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% out = deconvtvl1(g, H, mu, opts)
% deconvolves image g by solving the following TV minimization problem
%
% min (mu/2) || Hf - g ||_1 + ||f||_TV
%
% where ||f||_TV = sqrt( a||Dxf||^2 + b||Dyf||^2 c||Dtf||^2),
% Dxf = f(x+1,y, t) - f(x,y... |
github | ZHANGXinxinPKU/motion-deblurring-master | newton_w.m | .m | motion-deblurring-master/code/code/newton_w.m | 534 | utf_8 | 9848dc97c18e75653f702f5d44e16436 |
function [w] = newton_w(v, beta, alpha, lambda_1, kernel_size)
% 2016/06/01 %%%%%%%%%%%%%%%%%%%%%%%%%%
[mask,mask_1] = compute_mask1(v,kernel_size);
iterations = 4;
x = v;
for a=1:iterations
fd = (alpha)*sign(x).*abs(x).^(alpha-1).*mask_1+beta*(x-v)+lambda_1*beta*mask.*x;
fdd = alpha*(alpha-1)*abs(x).^(alpha... |
github | ZHANGXinxinPKU/motion-deblurring-master | tsmooth.m | .m | motion-deblurring-master/code/code/tsmooth.m | 4,449 | utf_8 | beef12196800f9e200139f18b34defe1 | function S = tsmooth(I,lambda,sigma,sharpness,maxIter)
%tsmooth - Structure Extraction from Texture via Relative Total Variation
% S = tsmooth(I, lambda, sigma, maxIter) extracts structure S from
% structure+texture input I, with smoothness weight lambda, scale
% parameter sigma and iteration number maxIter.
% ... |
github | ZHANGXinxinPKU/motion-deblurring-master | estimate_psf.m | .m | motion-deblurring-master/code/code/estimate_psf.m | 989 | utf_8 | 05487c7df60bc6ab914aeb0a87003964 | function psf = estimate_psf(blurred_x, blurred_y, latent_x, latent_y, weight, psf_size)
%2013/5/31 %%%%%%%%%%%%%%%%%%%%%%%%%
gamma = 10;
dx = [-1 1; 0 0];
dy = [-1 0; 1 0];
latent_xf = fft2(latent_x);
latent_yf = fft2(latent_y);
blurred_xf = fft2(blurred_x);
blurred_yf = fft2(blurred_y);
b_f =... |
github | ZHANGXinxinPKU/motion-deblurring-master | deblurring.m | .m | motion-deblurring-master/code/code/deblurring.m | 3,520 | utf_8 | 0ca49958dd0832cf5ff314667bd97bf6 | function [kernel, interim_latent] = deblurring(y, opts)
% 2016/06/01 %%%%%%%%%%%%%%%%%%%%%%%%%%%
% Deconvolution
% Pan's code
%%
% iteration
ret = sqrt(0.5);
maxitr=max(floor(log(5/min(opts.kernel_size))/log(ret)),0);
num_scales = maxitr + 1;
fprintf('Maximum iteration level is %d\n', num_scales);
%%
retv=ret.^[0:m... |
github | ZHANGXinxinPKU/motion-deblurring-master | deblurring_adm_aniso_1.m | .m | motion-deblurring-master/code/code/deblurring_adm_aniso_1.m | 1,390 | utf_8 | 31c45f8e82a4f8c51bc1f187bbfb3d0f | function [I] = deblurring_adm_aniso_1(B, k, lambda, alpha, lambda_1, kernel_size)
% 2016/06/01 %%%%%%%%%%%%%%%%%%%%%%%%%%
% reference: Pan's code
beta = 1/lambda;
beta_min = 0.001;
[m n] = size(B);
% initialize with input or passed in initialization
I = B;
% make sure k is a odd-sized
if ((mod(size(k, 1), 2) ~= ... |
github | ZHANGXinxinPKU/motion-deblurring-master | wrap_boundary_liu.m | .m | motion-deblurring-master/code/code/cho_code/wrap_boundary_liu.m | 3,568 | utf_8 | 778eb4d6eeeb26991f536cb17154be69 | function ret = wrap_boundary_liu(img, img_size)
% wrap_boundary_liu.m
%
% pad image boundaries such that image boundaries are circularly smooth
%
% written by Sunghyun Cho (sodomau@postech.ac.kr)
%
% This is a variant of the method below:
% Reducing boundary artifacts in image deconvolution
% Renting Liu, J... |
github | ZHANGXinxinPKU/motion-deblurring-master | adjust_psf_center.m | .m | motion-deblurring-master/code/code/cho_code/adjust_psf_center.m | 1,453 | utf_8 | ffd7dc5a8dc7589030f98a822f6b7c9a | function psf = adjust_psf_center(psf)
[X Y] = meshgrid(1:size(psf,2), 1:size(psf,1));
xc1 = sum2(psf .* X);
yc1 = sum2(psf .* Y);
xc2 = (size(psf,2)+1) / 2;
yc2 = (size(psf,1)+1) / 2;
xshift = round(xc2 - xc1);
yshift = round(yc2 - yc1);
psf = warpimage(psf, [1 0 -xshift; 0 1 -yshift]);
function val = sum2(arr)
val =... |
github | wrf-model/WRF-master | util.m | .m | WRF-master/chem/KPP/kpp/kpp-2.1/util/util.m | 1,409 | utf_8 | a200795ced439291d346b29e1b30b1ad | % ****************************************************************
%
% InitSaveData - Opens the data file for writing
%
% ****************************************************************
function InitSaveData ()
global KPP_ROOT_FID
KPP_ROOT_FID = fopen('KPP_ROOT.dat','w');
return %... |
github | wrf-model/WRF-master | Template_Fun_Chem.m | .m | WRF-master/chem/KPP/kpp/kpp-2.1/util/Template_Fun_Chem.m | 506 | utf_8 | 537cf51834cd520a33ee2c58c6f47578 |
% Wrapper for calling the ODE function routine
% in a format required by Matlab's ODE integrators
function P = KPP_ROOT_Fun_Chem(T, Y)
global TIME FIX RCONST
Told = TIME;
TIME = T;
KPP_ROOT_Update_SUN;
KPP_ROOT_Update_RCONST;
% This line calls the Matlab ODE function routine
P = KPP_ROOT_... |
github | wrf-model/WRF-master | Template_Jac_Chem.m | .m | WRF-master/chem/KPP/kpp/kpp-2.1/util/Template_Jac_Chem.m | 1,073 | utf_8 | 8fb398675e182b1e9a5449c11fa4f573 |
% Wrapper for calling the sparse ODE Jacobian routine
% in a format required by Matlab's ODE integrators
function J = KPP_ROOT_Jac_Chem(T, Y)
global TIME FIX RCONST
% To call the mex file uncomment one of the following lines:
% 1) LU prefix if SPARSE_LU_ROW option was used in code generation
% global ... |
github | jimmie33/Caffe-ExcitationBP-master | classification_demo.m | .m | Caffe-ExcitationBP-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | ArashAkbarinia/BoundaryDetection-master | SurroundModulationEdgeDetector.m | .m | BoundaryDetection-master/src/matlab/SurroundModulationEdgeDetector.m | 9,594 | utf_8 | 75800cc4a74161b45d48607c682cc4e5 | function EdgeImageResponse = SurroundModulationEdgeDetector(InputImage)
%SurroundModulationEdgeDetector computed the edges of an image.
%
% inputs
% InputImage the input image.
%
% outputs
% EdgeImageResponse the edges of input image.
%
% This is the supplementary material of our article presented at the
% IJCV'... |
github | vvanirudh/DPGP-master | sparseGP_predict_distri.m | .m | DPGP-master/sparseGP_predict_distri.m | 1,472 | utf_8 | 5df8b5776a4ba66b0dad5630248a556a | % current distribution: N(pos, pos_var)
% model: sparseGP
% return: prediction after dt
function [mu, var]= sparseGP_predict_distri(sparseGP, pos, pos_var)
W = [sparseGP.hyperparam(1)^2, 0; 0, sparseGP.hyperparam(2)^2];
W_inv = [sparseGP.hyperparam(1)^(-2), 0; 0, sparseGP.hyperparam(2)^(-2)];
I = eye(2);
... |
github | vvanirudh/DPGP-master | GP_predict.m | .m | DPGP-master/GP_predict.m | 1,302 | utf_8 | 7e2b19f056fdb22f1ff4bf0413f543ec | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 16.322 Stochastic Estimation
% Gaussian Process
% prediction using Gaussian kernal
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [mu, var_f] = GP_predict(x_obs, y_obs, speed, x_query, y_query, hyperparam)
% compute C
C = Gaussian_kernel(x_obs, y_obs, x_o... |
github | vvanirudh/DPGP-master | groupTraj.m | .m | DPGP-master/DP/groupTraj.m | 1,771 | utf_8 | 71900747f6734aabe965a445874254c7 | function count = groupTraj(sweep_count)
%fprintf('in groupTraj function, sweep number: %d', sweep_count);
global trajs sparseGPs
% preprocessing: remove empty clusters
[c, ia, ic] = unique(trajs.cluster(:,sweep_count));
[c_sort, c_ind] = sort(c);
trajs.cluster(:,sweep_count) = c_ind(ic);
trajs.cluster(:,sweep_co... |
github | vvanirudh/DPGP-master | predPlot.m | .m | DPGP-master/plotting/predPlot.m | 1,774 | utf_8 | 9ff8d6946d6c400fc601cf3a47f51e23 | function predPlot(pred_traj, sparseGP_x, sparseGP_y)
addpath ../
x = pred_traj(:,1);
y = pred_traj(:,2);
sigma_x = sqrt(pred_traj(:,3));
sigma_y = sqrt(pred_traj(:,4));
x_min = min(sparseGP_x.x_data)-1;
x_max = max(sparseGP_x.x_data)+1;
y_min = min(sparseGP_x.y_data)-1;
y_max = max(sparseGP_x.y_data)+1;
... |
github | vvanirudh/DPGP-master | plotTrajs.m | .m | DPGP-master/plotting/plotTrajs.m | 1,894 | utf_8 | 6fcb207a0c289c877fa9cef3510a3ebd | function plotTrajs(trajs, string_in)
n_trajs = trajs.n_traj;
colors = {'r','b','g','y','m','c','k'};
figure
hold on
num_group_per_subplot = 7;
num_cluster = max(trajs.cluster(:,end));
% trajs with cluster assignment 0 are singleton clusters
ifRemove = 1-min(trajs.cluster(:,end));
num_figure = ceil(num_clu... |
github | vvanirudh/DPGP-master | twoagents_findBestPattern.m | .m | DPGP-master/Cooperative/twoagents_findBestPattern.m | 1,568 | utf_8 | 81378486662708d96064c995447d3a6b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to find the best cluster pair
% that fits the current pair of trajectories
% by Anirudh Vemula, Jul 21, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ind1, ind2] = twoagents_findBestPattern(traj1, ...
tra... |
github | vvanirudh/DPGP-master | DP_traj_likelihood_dep.m | .m | DPGP-master/Cooperative/DP_traj_likelihood_dep.m | 2,067 | utf_8 | 42a136a71a027d2fe76304831b4451ff | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to compute the likelihood
% p(t2 | t1, b_j1, b_j2)
% by Anirudh Vemula, Jul 20, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [likelihood l_vector] = DP_traj_likelihood_dep(sparseGP_x_2, ...
sparseGP_y_2, ...
... |
github | vvanirudh/DPGP-master | twoagents_groupTraj.m | .m | DPGP-master/Cooperative/twoagents_groupTraj.m | 3,131 | utf_8 | 460fe7353c09f7d1866c48a9702cdf11 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to group two agent trajectories
% by Anirudh Vemula, Jul 19, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function count = twoagents_groupTraj(sweep_count)
global trajs sparseGPs
% preprocessing: remove empty clusters
[c, ia, ic] = unique(trajs.cluster(:, :, sweep_count))... |
github | vvanirudh/DPGP-master | twoagents_plotTrajs.m | .m | DPGP-master/Cooperative/twoagents_plotting/twoagents_plotTrajs.m | 2,647 | utf_8 | e191588d8f9d5136ad33b6106e13083b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to plot the trajectories
% in the two agents case
% by Anirudh Vemula, Jul 21, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function twoagents_plotTrajs(trajs, string_in)
n_trajs = trajs.n_traj;
colors = {'r','b','g','y','m','c','k'};
figure;
hold on... |
github | vvanirudh/DPGP-master | generateTwoAgentTrajs.m | .m | DPGP-master/Cooperative/genTraj/generateTwoAgentTrajs.m | 2,489 | utf_8 | 2c8572d00c6572581c2df9ae4ac80f3b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to generate n trajectories of
% two interacting agents. For now modeling
% cooperative collision avoidance
% by Anirudh Vemula, Jul 18, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function trajs = generateTwoAgentTrajs(n_traj, n_points, pLimit, ...
... |
github | vvanirudh/DPGP-master | moveAgent.m | .m | DPGP-master/Cooperative/genTraj/moveAgent.m | 694 | utf_8 | c74eec339c8bc8eed02e34e6eddacbe8 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to move agent using quadratic
% interpolation
% by Anirudh Vemula, Jul 25, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function x2_new = moveAgent(x1, x2, ind, threshold)
% Function always assumes that agent 2 has to be moved w.r.t agent 1
x2_new = x2;
if x1(in... |
github | vvanirudh/DPGP-master | generateTwoAgentTraj.m | .m | DPGP-master/Cooperative/genTraj/generateTwoAgentTraj.m | 1,915 | utf_8 | bb1d2876f8d281d77da8361f041533a7 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to generate a pair of trajectories
% for two agents, that model cooperative
% collision avoidance (if needed)
% by Anirudh Vemula, Jul 18, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [x1, y1, x2, y2, dt1, dt2] = generateTwoAgentTraj(n, pLimit, ..... |
github | vvanirudh/DPGP-master | processTwoAgentTraj.m | .m | DPGP-master/Cooperative/genTraj/processTwoAgentTraj.m | 1,007 | utf_8 | a6eb4e6bd7322c786f606942d8defee2 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to process a trajectory
% by Anirudh Vemula, Jul 19, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [x, y, dx_dt, dy_dt] = processTwoAgentTraj(x, y, dt, ...
sigma_noise)
% Length of trajectory
n = l... |
github | vvanirudh/DPGP-master | findTrajPosition.m | .m | DPGP-master/Cooperative/genTraj/findTrajPosition.m | 550 | utf_8 | e0bae6bbd9d6760d345298f538cc4c22 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Function to find the position in the trajectory
% corresponding to a given timestep
% by Anirudh Vemula, Jul 21, 2016
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [x, y] = findTrajPosition(traj, t)
% Construct the cumulative time array
cum_t = cumsum(t... |
github | vvanirudh/DPGP-master | gibbs_sampling_postProcessing.m | .m | DPGP-master/Gibbs/gibbs_sampling_postProcessing.m | 1,127 | utf_8 | 358366768cb1723279fe6a9b5d74f155 | % cluster
% burn_in
% splicing
function [avgSample, mode, config, config_count] = gibbs_sampling_postProcessing(cluster, burn_in, splicing)
% % burn in
cluster_p = cluster(burn_in+1:end,:);
% splicing
cluster_p = cluster_p(1:splicing:end,:);
% reordering
[m n] = size(cluster_p);
for i = 1:m
cluster_... |
github | vvanirudh/DPGP-master | pinky.m | .m | DPGP-master/external/pinky.m | 7,068 | utf_8 | b4f861ec361ebdb4e64ef0e06845253e | %Tristan Ursell
%2D Random Number Generator for a Given Discrete Distribution
%March 2012
%
%[x0,y0]=pinky(Xin,Yin,dist_in,varargin);
%
%'Xin' is a vector specifying the equally spaced values along the x-axis.
%
%'Yin' is a vector specifying the equally spaced values along the y-axis.
%
%'dist_in' (dist_in > ... |
github | jbukala/heart_rate_head_motion-master | disp_hhs.m | .m | heart_rate_head_motion-master/MATLABfiles/MEMD/disp_hhs.m | 1,688 | utf_8 | 17bc1c9b5b21cfccf3f7eed5128a530c | %DISP_HHS display Hilbert-Huang spectrum
%
% DISP_HHS(im,t,inf,fs)
% displays in a new figure the spectrum contained in matrix "im"
% (amplitudes in dB).
%
% inputs: - im: image matrix (e.g., output of "toimage")
% - t (optional): time instants (e.g., output of "toimage")
% - inf (optional): -dynam... |
github | jbukala/heart_rate_head_motion-master | memd.m | .m | heart_rate_head_motion-master/MATLABfiles/MEMD/memd.m | 18,989 | utf_8 | 6cb333549d773095fa226245e38f4882 | function q = memd(x, varargin)
%
%
% function MEMD applies the "Multivariate Empirical Mode Decomposition" algorithm (Rehman and Mandic, Proc. Roy. Soc A, 2010)
% to multivariate inputs. We have verified this code by simulations for signals containing 3-16 channels.
%
% Syntax:
%
% imf = MEMD(X)
% returns a 3D matrix... |
github | jbukala/heart_rate_head_motion-master | plot_coupling.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/plot_coupling.m | 7,793 | utf_8 | 721165578e75e07535d2d49321079181 | function plot_coupling(data,locs,pars);
% usage plot_coupling(data,locs,pars);
% makes head-in-head plots
% data is an NxN matrix where N is the number of channels
% locs is (ideally) an Nx5 matrix:
% 1st column: a channel i gets a circle only if locs(i,1)>.5
% if locs is an Mx5 matrix with M<N
%... |
github | jbukala/heart_rate_head_motion-master | plot_coherence_rand.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/plot_coherence_rand.m | 7,599 | utf_8 | 921d0c2bb997539fb9dfb5bf194b202b | function plot_coherence(data,locs,pars);
% usage plot_coherence(data,locs,pars);
% makes head-in-head plots
% data is an NxN matrix where N is the number of channels
% locs is (ideally) an Nx5 matrix:
% 1st column: a channel i gets a circle only if locs(i,1)>.5
% if locs is an Mx5 matrix with M<N... |
github | jbukala/heart_rate_head_motion-master | locphys2locphys.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/locphys2locphys.m | 4,187 | utf_8 | ac49b116af7bbff4c6fb072f3466800f | function [loc_phys,names]=locphys2locphys(loc_phys_in);
% Purpose: create 'physical' locations from neoroscan-data
%
% usage: [loc_phys,names]=loc2locphys(fn,ind_phys,loctype)
%
% output: loc_phys nX5 matrix; each row contains information
% about a physical electrode in the form
% ... |
github | jbukala/heart_rate_head_motion-master | showfield_general.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/showfield_general.m | 2,574 | utf_8 | ffae1806380a13d020cee099fab2f8b6 | function showfield_general(z,loc,pars);
% usage showfield_general(z,loc);
% displays fields/potentials specified z in channels at locations
% specified in locs as a contour-plot
%
% pars is optional
% pars.scale sets the scale of the color map. Either a 1x2 vector
% corresponding to minimum and a maximum o... |
github | jbukala/heart_rate_head_motion-master | plot_coherence_dots.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/plot_coherence_dots.m | 8,686 | utf_8 | ef427a547b421bf6c1e5cefc9063a21b | function plot_coherence_dots(data,locs,pars);
% usage plot_coherence(data,locs,pars);
% makes head-in-head plots
% data is an NxN matrix where N is the number of channels
% locs is (ideally) an Nx5 matrix:
% 1st column: a channel i gets a circle only if locs(i,1)>.5
% if locs is an Mx5 matrix wit... |
github | jbukala/heart_rate_head_motion-master | sphfit.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t501_VisualizeCoupling/sphfit.m | 1,907 | utf_8 | 545ad59afcaa98465201834183b866f3 | function [center,radius]=sphfit(vc)
% SPHFIT fits a sphere to a set of surface points
%
% input:
% vc nx3 matrix, where each row represents the location
% of one surface point. vc can have more than 3 columns
% (e.g. orientations) - then only the first 3 columns are used
%
% center 1x3 vector denoting th... |
github | jbukala/heart_rate_head_motion-master | scpopen.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t200_FileAccess/scpopen.m | 57,414 | utf_8 | 07d0eac972f4f7c4aeac8e7db6bd1180 | function [HDR]=scpopen(arg1,CHAN,arg4,arg5,arg6)
% SCPOPEN reads and writes SCP-ECG files
%
% SCPOPEN is an auxillary function to SOPEN for
% opening of SCP-ECG files for reading ECG waveform data
%
% Use SOPEN instead of SCPOPEN
%
% See also: fopen, SOPEN,
% $Id$
% (C) 2004,2006,2007,2008 by Alois Schloegl <a... |
github | jbukala/heart_rate_head_motion-master | openxml.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t200_FileAccess/openxml.m | 13,850 | utf_8 | a2522f85226716568c1d40ee7e6666f6 | function [HDR]=openxml(arg1,CHAN,arg4,arg5,arg6)
% OPENXML reads XML files and tries to extract biosignal data
%
% This is an auxilary function to SOPEN.
% Use SOPEN instead of OPENXML.
%
%
% HDR = openxml(HDR);
%
% HDR contains the Headerinformation and internal data
%
% see also: SOPEN, SREAD, SSEEK, STELL, SCLOSE,... |
github | jbukala/heart_rate_head_motion-master | matread.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t200_FileAccess/matread.m | 10,223 | utf_8 | a5989a133cd8aa5fc2b1e3e9d1dba904 | function [HDR,data,t]=matread(HDR,arg2,idxlist)
% MATRREAD Loads (parts of) data stored in Matlab-format
%
% [HDR,data,timeindex]=matread(HDR,block_number, [startidx, endidx])
% This is the recommended use for Matlab-files generated from ADICHT data
% Before using MATREAD, HDR=MATOPEN(filename, 'ADI', ...) must be app... |
github | jbukala/heart_rate_head_motion-master | eegplugin_biosig.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/eeglab/eegplugin_biosig.m | 3,624 | utf_8 | 98dba671b6281727ca315d2f5551a94e | % eegplugin_biosig() - EEGLAB plugin for importing data using BIOSIG Matlab toolbox
%
% Usage:
% >> eegplugin_biosig(fig, trystrs, catchstrs);
%
% Inputs:
% fig - [integer] EEGLAB figure
% trystrs - [struct] "try" strings for menu callbacks.
% catchstrs - [struct] "catch" strings for menu callbacks.... |
github | jbukala/heart_rate_head_motion-master | pop_readbdf.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/eeglab/pop_readbdf.m | 8,545 | utf_8 | 5469849667b4be27f91c2ced20e8b954 | % pop_readbdf() - Read Biosemi 24-bit BDF file
%
% Usage:
% >> EEG = pop_readbdf; % an interactive window pops up
% >> EEG = pop_readbdf( filename ); % no pop-up window
% >> EEG = pop_readbdf( filename, range, eventchans, ref );
%
% Graphical interface:
% "Data block range to read" - {edit box] se... |
github | jbukala/heart_rate_head_motion-master | pop_readedf.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/eeglab/pop_readedf.m | 3,977 | utf_8 | 5a1f3e3710cfeff03e075a8c07cdcab9 | % pop_readedf() - Read a European data format .EDF data file.
%
% Usage:
% >> EEG = pop_readedf; % an interactive window pops up
% >> EEG = pop_readedf( filename ); % no pop-up window
%
% Inputs:
% filename - European data format 16-bit EDF file
%
% Outputs:
% EEG - EEGLAB data ... |
github | jbukala/heart_rate_head_motion-master | pop_biosig.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/eeglab/pop_biosig.m | 4,988 | utf_8 | f7d5b0c8e894b15e97782834a472e1b8 | % pop_biosig() - import data files into EEGLAB using BIOSIG toolbox
%
% Usage:
% >> OUTEEG = pop_biosig; % pop up window
% >> OUTEEG = pop_biosig( filename, channels, type);
%
% Inputs:
% filename - [string] file name
% channels - [integer array] list of channel indices
% type - [string] file type. See sl... |
github | jbukala/heart_rate_head_motion-master | nqrsdetect.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t300_FeatureExtraction/nqrsdetect.m | 12,010 | utf_8 | dfd16e72af64c755bd520423735d53ec | function QRS = nqrsdetect(S,fs);
% nqrsdetect - detection of QRS-complexes
%
% QRS=nqrsdetect(S,fs);
%
% INPUT
% S ecg signal data
% fs sample rate
%
% OUTPUT
% QRS fiducial points of qrs complexes
%
%
% see also: QRSDETECT
%
% Reference(s):
% [1]: V. Afonso, W. Tompkins, T. Nguyen, and S. Luo, ... |
github | jbukala/heart_rate_head_motion-master | qrscorr.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t300_FeatureExtraction/qrscorr.m | 11,064 | utf_8 | 73a48661bed0782013b319e467310a4e | function [QRStime_corr,dr,dr_corr,U,ANNOT] = QRScorr(QRSindex,Fs,Nmax);
% Identification and correction of detection errors on QRS-beat sequences
%
% This algorithm identifies anomalies like FP, FN or ectopic beats.
% The FP and FN are corrected by deleting or inserting one or multiple beats.
%
% INPUT:
% QRSindex: ... |
github | jbukala/heart_rate_head_motion-master | hurst.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t300_FeatureExtraction/hurst.m | 1,747 | utf_8 | f36b269b6ee9ccb711eadc8bf0110dd6 | %% Copyright (C) 1995, 1996, 1997 Friedrich Leisch
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.... |
github | jbukala/heart_rate_head_motion-master | remNoiseTF.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t320_Nirs/remNoiseTF.m | 5,489 | utf_8 | 087cbf2f8bf400f57be26a279024cb12 | function corrSignal=remNoiseTF(signal,noise,fs,windowlength)
%
% remNoiseTF removes respiration an blood pressure related noise from
% [(de)oxy-Hb] signals by using a transfer function model [1,2]. For a detailed
% description of the model see [3].
%
% [corrSignal]=remNoiseTF(signal,noise,fs,shift)
%
% Input:
% s... |
github | jbukala/heart_rate_head_motion-master | train_sc.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/t400_Classification/train_sc.m | 38,368 | utf_8 | 78f47a549cfe60632399a714044de38c | function [CC]=train_sc(D,classlabel,MODE,W)
% Train a (statistical) classifier
%
% CC = train_sc(D,classlabel)
% CC = train_sc(D,classlabel,MODE)
% CC = train_sc(D,classlabel,MODE, W)
% weighting D(k,:) with weight W(k) (not all classifiers supported weighting)
%
% CC contains the model parameters of a classifier w... |
github | jbukala/heart_rate_head_motion-master | isdir.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/isdir.m | 864 | utf_8 | cb1ff118a492dd2f2e6e2c6df4db7cab | ## Copyright (C) 2004 Alois Schloegl
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distr... |
github | jbukala/heart_rate_head_motion-master | wilcoxon_test.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/wilcoxon_test.m | 3,003 | utf_8 | 785cb0c5004ed932a442fea86f68b52a | %% Copyright (C) 1995, 1996, 1997 Kurt Hornik
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%... |
github | jbukala/heart_rate_head_motion-master | flops.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/flops.m | 863 | utf_8 | acc5af64fabf799431a2c3b568ee4825 | %% Copyright (C) 2004 Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distr... |
github | jbukala/heart_rate_head_motion-master | isequal3.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/isequal3.m | 6,725 | utf_8 | c3a44d26a3451aabd832fd1471f80789 | %% Copyright (C) 2000, 2005, 2006, 2007 Paul Kienzle
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 3 of the License, or (at
%% your option) an... |
github | jbukala/heart_rate_head_motion-master | strtok.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strtok.m | 4,016 | utf_8 | 343c3e4f44c87e4bdcdc196330d152cb | %% Copyright (C) 2000 Paul Kienzle
%% Copyright (C) 2008 Alois Schloegl
%% $Id: strtok.m,v 1.2 2008-01-19 20:31:52 schloegl Exp $
%% This function is part of BioSig http://biosig.sf.net
%% Originally, it was part of Octave. It was modified for the use with FreeMat
%%
%%
%% This program is free software; you can redist... |
github | jbukala/heart_rate_head_motion-master | strvcat.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strvcat.m | 2,438 | utf_8 | 2a9e59852f342da41b6b676aba9e7eb1 | %% Copyright (C) 1996 Kurt Hornik
%%
%% This program is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%% This program is distributed in the hope ... |
github | jbukala/heart_rate_head_motion-master | betapdf.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/betapdf.m | 1,845 | utf_8 | b3277cfe86c485b62d558c2c0f1b667f | %% Copyright (C) 1995, 1996, 1997 Kurt Hornik
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%... |
github | jbukala/heart_rate_head_motion-master | spdiag.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/spdiag.m | 967 | utf_8 | 898b022e9979f5ffdd3d89893dac081f | %% Copyright (C) 2007 Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distr... |
github | jbukala/heart_rate_head_motion-master | isscalar.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/isscalar.m | 1,131 | utf_8 | b75059e3787f8a05e8b157758d66c468 | %% Copyright (C) 1996, 1997 John W. Eaton
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%% Oct... |
github | jbukala/heart_rate_head_motion-master | unique.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/unique.m | 3,230 | utf_8 | a8cf7482ff441f6f4b9f71cb0138267c | %% Copyright (C) 2000-2001 Paul Kienzle
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is dis... |
github | jbukala/heart_rate_head_motion-master | betacdf.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/betacdf.m | 1,873 | utf_8 | b6cffc54fc3c67de098b78cfff4da4e3 | %% Copyright (C) 1995, 1996, 1997 Kurt Hornik
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%... |
github | jbukala/heart_rate_head_motion-master | binocdf.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/binocdf.m | 1,940 | utf_8 | 447b603d6c6698f55df0f6182dff1589 | %% Copyright (C) 1995, 1996, 1997 Kurt Hornik
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%... |
github | jbukala/heart_rate_head_motion-master | strncmp.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strncmp.m | 1,573 | utf_8 | 121755f629a95d9866448a7194ccb7d8 | %% Copyright (C) 2000 Bill Lash
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distribute... |
github | jbukala/heart_rate_head_motion-master | strmatch.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strmatch.m | 1,921 | utf_8 | f94bbd2c6085e1894851d1a8a2e9c210 | %% Copyright (C) 2000 Paul Kienzle
%% Jun 2003 Alois Schloegl, support for cell arrays.
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% ... |
github | jbukala/heart_rate_head_motion-master | datenum.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/datenum.m | 2,676 | utf_8 | 548c2bc7e92a54db03be897dbc0ee1a8 | %% -*- texinfo -*-
%% @deftypefn {Function File} {} datenum(Y, M, D [, h , m [, s]])
%% @deftypefnx {Function File} {} datenum('date' [, P])
%% Returns the specified local time as a day number, with Jan 1, 0000
%% being day 1. By this reckoning, Jan 1, 1970 is day number 719529.
%% The fractional portion, corresponds... |
github | jbukala/heart_rate_head_motion-master | strcmpi.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strcmpi.m | 1,334 | utf_8 | 5c48e9fcce0d52419bc07e2dbae39546 | %% Copyright (C) 2000 Bill Lash
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distribute... |
github | jbukala/heart_rate_head_motion-master | setstr.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/setstr.m | 843 | utf_8 | e2d245f23bd347fe23bbf78313ab0dcf | %% Copyright (C) 2007 Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distr... |
github | jbukala/heart_rate_head_motion-master | u_test.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/u_test.m | 3,010 | utf_8 | e8481a42a619b4c595ee8b07c579811f | %% Copyright (C) 1995, 1996, 1997 Kurt Hornik
%%
%% This file is part of Octave.
%%
%% Octave is free software; you can redistribute it and/or modify it
%% under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2, or (at your option)
%% any later version.
%%
%... |
github | jbukala/heart_rate_head_motion-master | strncmpi.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strncmpi.m | 1,382 | utf_8 | 24b0d2559350ca14ef8adbd741a8db0f | ## Copyright (C) 2000 Bill Lash
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distribute... |
github | jbukala/heart_rate_head_motion-master | betarnd.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/betarnd.m | 3,055 | utf_8 | c65a4be7562cb9c75e00627dfd984f47 | ## Copyright (C) 1995, 1996, 1997 Kurt Hornik
##
## This file is part of Octave.
##
## Octave is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2, or (at your option)
## any later version.
##
#... |
github | jbukala/heart_rate_head_motion-master | strfind.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strfind.m | 2,280 | utf_8 | ccdd230eda0a7eefa5f3fb07cbfd2540 | %% Copyright (C) 2004 by Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or
%% modify it under the terms of the GNU General Public License
%% as published by the Free Software Foundation; either version 3
%% of the License, or (at your option) any later version.
%%
%% This program is dis... |
github | jbukala/heart_rate_head_motion-master | datestr.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/datestr.m | 7,247 | utf_8 | 82de9e774a74a995df453eb191747816 | ## Copyright (C) 2000 Paul Kienzle
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distribu... |
github | jbukala/heart_rate_head_motion-master | int2str.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/int2str.m | 853 | utf_8 | 9d0a536a1256406a26d86f2a50a73a28 | %% Copyright (C) 2007 Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distr... |
github | jbukala/heart_rate_head_motion-master | barh.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/barh.m | 3,377 | utf_8 | 6540aec6c9a64c8cb34a575bc482eefb | ## Copyright (C) 1996, 1997 John W. Eaton
##
## This file is part of Octave.
##
## Octave is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2, or (at your option)
## any later version.
##
## Oct... |
github | jbukala/heart_rate_head_motion-master | datesplit.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/datesplit.m | 14,264 | utf_8 | 99ecb4dbb463adf8c545023aa2a2f993 | ## Copyright (C) 2001 Bill Denney <bill@givebillmoney.com>
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## ... |
github | jbukala/heart_rate_head_motion-master | full.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/full.m | 887 | utf_8 | 4deef0ec2dc43289a0f7b8189659af46 | %% Copyright (C) 2007 Alois Schloegl
%%
%% This program is free software; you can redistribute it and/or modify
%% it under the terms of the GNU General Public License as published by
%% the Free Software Foundation; either version 2 of the License, or
%% (at your option) any later version.
%%
%% This program is distr... |
github | jbukala/heart_rate_head_motion-master | strfind2.m | .m | heart_rate_head_motion-master/MATLABfiles/biosig/maybe-missing/strfind2.m | 2,802 | utf_8 | 95fffff02c8cfa7afcdd3f4ff4bdfb39 | ## Copyright (C) 2004 by Alois Schloegl
##
## This program is free software; you can redistribute it and/or
## modify it under the terms of the GNU General Public License
## as published by the Free Software Foundation; either version 2
## of the License, or (at your option) any later version.
##
## This program is dis... |
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