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function lkDpxTuningExp(varargin)
% lkDpxTuningExp(varargin)
%
% EXAMPLES
% Standard grating tuning curve:
% lkDpxTuningExp
% Grating speed tuning curve with different contrasts vertical
% lkDpxTuningExp('mode','Speed', 'stim','Grat', 'dirdeg',90)
% Random dots speed t... |
function [x,xp] = twalkEnds(xxp)
n=size(xxp,1)/2;
x=xxp(1:n,end);
xp=xxp(n+(1:n),end);
end |
function [J grad] = rnaCusto(nn_params, ...
input_layer_size, ...
hidden_layer_size, ...
num_labels, ...
X, y, lambda)
%RNACUSTO Implementa a funcao de custo para a rede neural com duas camadas
%voltada p... |
clc;close all;clear all
% lenght for testing
n = 500;
% Modeling signal
Y1 = (0.5 .* sin((1:2500)/2));
Y2 = (0.5 .* sin((1:2500)/10));
Y = [Y1 Y2];
U = [ones(1,2500) 2*ones(1,2500)];
% create data for testing
Yz = [Y1(1:(n/2)) Y2(1:(n/2))];
Uz = [ones(1,(n/2)) 2*ones(1,(n/2))];
figure('Color','w');
plot(Yz,'k');hold... |
function [x,y] = findK
%%%%%%%%%%%%%%%%%%%%%%%%%
% READING IN DATA %%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%
% Initialize Questionnaire Data
% Four columns:
% 1. Order
% 2. SIR (small immediate reward)
% 3. LDR (large delayed reward)
% 4. Delay
qdat = readtable('kirby.csv');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SIMUL... |
C1 = [2,1;1,2];
C2 = [2,1;1,2];
m1 = [0;2];
m2 = [1.7;2.5];
numGrid = 50;
xRange = linspace(-6.0, 6.0, numGrid);
yRange = linspace(-6.0, 6.0, numGrid);
P1 = zeros(numGrid, numGrid);
P2 = P1;
for i = 1:numGrid
for j = 1:numGrid
x = [yRange(j) xRange(i)]';
P1(i,j) = mvnpdf(x', m1', C1);
... |
clear all;
close all;
alpha=load('hur_data');
iters=2;
sigma=[0 2 5 10 20];
RunL=1000;
err=zeros(iters,RunL);
A=[1 -10;10 1];
for j=1:5
fptr=fopen(strcat('hur',num2str(j)),'w');
err=zeros(iters,RunL);
for i=1:iters
[err(i,:)]=construn(A,sigma(j),alpha(j,2),RunL);
end;
err_mean=mean(err);
err_std=std(err);
... |
%*******************************************************************
% Region Based Stereo Matching Algorithm by Global Error Energy
% Minimization by Smoothing Functions method explanied in the
% "Obtaining Depth Maps From Color Images By Region Based Stereo
% Matching Algorithms"
%
% It uses stereo color ima... |
function lengths = grEdgeLength(nodes, edges, varargin)
%GREDGELENGTH Compute length of edges in a geometric graph.
%
% Deprecated, use 'grEdgeLengths' instead.
%
% LENGTHS = grEdgeLength(NODES, EDGES)
%
% Example
% grEdgeLength
%
% See also
% grEdgeLenghts
% ------
% Author: David Legland... |
function make25Hzraw(tag)
%
% make25Hzraw(tag)
%
[s,fs]=swvread(tag,[],2) ;
save(['/tag/data/raw/' tag 'raw25'],'s','fs')
|
function result = Runge_Kuuta(start,finish,stride,u0)%依次是 起点,终点,步长.
%题目要求四级四阶方法,对应 m = 4 , f = tu^2
u0 = 1 ; %给定初始值
t = start;%t(0)
n = (finish - start)/stride;%结点数
u=[];u(1) = u0;%u(1)实际的u(0)
for i = 1:n
k1 = t*u(i)^2;
k2 = (t + stride/2)*( u(i) + stride/2 * k1)^2;
k3 = (t + stride/2)*( u(i) + strid... |
function [ output_args ] = testhypergraph( input_args )
%TESTHYPERGRAPH Summary of this function goes here
% Detailed explanation goes here
H= [0 1 0 0 0 1;
1 0 1 0 1 1;
1 0 0 1 1 0;
1 1 1 0 1 1;
0 1 2 1 1 1;
1 0 1 1 0 1];
Dvm = diag(sum(H,2))
Dem = diag(sum(H,1))
Dwm = eye(6);
A=Dvm^(-1/2)*H*D... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright ?2011,2012 Yuchao Dai, Hongdong Li, Mingyi He
% This file is part of NRSFM_DLH.
%
% NRSFM_DLH is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as p... |
function [Delta,beta] = cnum2sys(delta0,w0)
% Delta = cnum2sys(delta0,w0)
%
% The complex number delta0 and frequency w0>0 are given.
% This function constructs a stable, LTI system Delta(s) such that
% Delta(j w0) = delta0 and || Delta \|_infty <= |delta0|
if isreal(delta0)
beta = 0;
Delta = ss([],[]... |
function [bin_NUB_len,final_emUBdata,tag_NUB1,tag_NUB2,tag_NUB3,tag_NUB4,tag_NUB5,tag_NUB6,tag_NUB7,tag_NUB8,Second_pro_bitplane1,Second_pro_bitplane2,Second_pro_bitplane3,Second_pro_bitplane4,Second_pro_bitplane5,Second_pro_bitplane6,Second_pro_bitplane7,Second_pro_bitplane8] = Preprocess2(compress_type_len,tag_prepro... |
function [M] = subsMatrix(N, pos, t1, t2, t3, t4, t5, t6)
% Calculates the numeric value of a symbolic matrix at a specific point.
% M is a 6x6 double
% N is a 6x6 sym
% pos is a 1x6 double of actuator angles
if(length(pos) ~= 6)
return;
end
t1 = pos(1); t2 = pos(2); t3 = pos(3);
t4 = pos(4); t5 = pos(5); t6 = p... |
function [RT] = rigbt(Phi, Psi, Theta, x0, y0, z0)
%刚体变换函数:rigid body transformation
%输入参数：
% φ=Phi 绕x轴转动的角度
% ψ=Psi 绕y轴转动的角度
% θ=Theta 绕z轴转动的角度
%输出参数：
% RT 将坐标轴进行刚体变化（旋转+平移）成新的坐标轴
%
%% 程序
R1 = [1 0 0; 0 cos(Phi) sin(Phi); 0 -sin(Phi) cos(Phi)];%绕X轴旋转
R2 = [cos(Psi) 0 -sin(Psi); 0 1 ... |
function pop = eraseWeak(pop,varargin)
% population/eraseWeak
%
% pop = eraseWeak(pop,N=1)
%
% Erases the weakest N individuals in the population.
%************************************************************
%* *
%* vgGA: The Virtual Gene Genetic Algorithm ... |
% UMI filter and plot
% remove UMIs w/ small number of counts; threshold determined by dynamic cutoff, top3 UMI family size does not distinguish different genotypes
clear all;
close all;
uniqUMInum1 = zeros(1,226);
uniqUMInum2 = zeros(1,226);
uniqUMInum3 = zeros(1,226);
uniqUMInum4 = zeros(1,226);
alignedreads = zeros... |
function [FBAsols,DRgenes,constrainedRxns,cycleStart,states] = optimizeRegModel(model,initialRegState)
% optimizeRegModel - finds the steady state solution of a model with
% Boolean regulatory constraints
%
% [FBAsols,DRgenes,constrainedRxns,cycleStart,states] = optimizeRegModel(model,initialRegState)
%
% model ... |
function [Gc,Kp,Ti,Td,H]=cohenpid(key,vars)
K=vars(1); L=vars(2); T=vars(3); N=vars(4);
a=K*L/T; tau=L/(L+T); H=[];
if key==1,
Kp=(1+0.35*tau/(1-tau))/a; Gc=tf(Kp,1);
elseif key==2,
Kp=0.9*(1+0.92*tau/(1-tau))/a;
Ti=(3.3-3*tau)*L/(1+1.2*tau);
Gc=tf(Kp*[Ti,1],[Ti,0]);
elseif key==3 | key==4
... |
%% second_level_MVPA
% Runs 1 sample t-test and/or displays results
%
% MM/DD/YY -- CHANGELOG
% 05/01/20 -- Log started, forked for MVPA
function second_level_MVPA(subj, study, dd, ss, classifier)
%% check inputs
if length(subj) < 2
error('Submit ALL subjects!')
end
if ~isstruct(subj) || ~isstruct(study)
er... |
function pic = PictureReader(index, p)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Read in a picture with the given index and folder name
%
% INPUTS:
% index - the # in the file name.
% p.smoothing - 0 if there should be no smoothing. 'n' if there should
% ... |
% Script to return a vector of coefficients of elastohydrodynamics modes of a
% slender rod for angle data
%chosenOnes = [3,4,7,32];
% Chosen ones for 560_lessthan_0.6tc(20170411T131818268)
chosenOnes = [49, 48, 45, 42, 34, 25, 20, 13, 11, 7, 6, 5, 4, 35, 22, 15, 3];
nmax = 3;
bcs = 'free'; % Only know free end stu... |
clear; clc;
fs = 10000;
recorder = audiorecorder(fs, 8,1);
recordblocking(recorder,2); %recorder turned ON for 2 seconds
play(recorder)
%y - Array to store the recorded data
y = getaudiodata(recorder);
filename = 'speech2.wav';
%Write data in y to .wav file
audiowrite('speech2.wav', y, 10000);
|
function [X] = unorigami( X, dim)
X = reshape(X, dim(1), []);
for i = dim(2)+1:2*dim(2):dim(2)*dim(3)
X(:,i:i+dim(2)-1)=fliplr(X(:,i:i+dim(2)-1));
end
end
|
function [config_clearance_value adj_list] = invalidBasedConfigsClearance(configs,adj_list,prm_distances,valid_nodes,invalid_nodes )
%Compute clearance of each configuration.
% Compute clearance of each configuration based on the distance from the
% nearest invalid configuration.
total_configs = size(configs,1);
... |
function [net, ehist, act] = train_srn(net, ipat, tpat)
% Train an SRN with one input, one hidden, and one output layer. The
% sigmoid function is used as the activation function of the hidden units.
% The softmax function is used as the activation function of the output
% units.
ninput = net.ninput;
nhid = net.nhid;
... |
% Sourced from "Pattern Recognition"
function [SVMstruct,svIndex,pe_tr,pe_te]=...
SVM_clas(X1,y1,X2,y2,tol,C,sigma)
options = statset('Display','iter',...
'MaxIter',20000);
%Training and Ploting parameters
[SVMstruct,svIndex]=svmtrain(X1, y1,...
'KERNEL_FUNCTION','rbf',...
'RBF_SIGMA',sigma,'BOXCONSTRAINT',C,'sh... |
function [ timeInfo ] = find_time( data )
%find_time It finds the time
%Initialize timeInfo
timeInfo = zeros(1,4);
%Define hundreds, tens, and ones matrices
hundreds = [200 100];
tens = [80 40 20 10];
ones = [8 4 2 1];
%Determine year using the dot product
yearTens = dot(tens, data(46:49));
yearOnes = dot(ones, dat... |
% Learning phase of trials
a=0
for a=0:2
visStim= fget1(a + '.txt')
audStim= read(a + '.wav')
display(visStim)
pause(1)
wavplay(audstim)
end
|
% V - różnica potencjałów między wewnętrzną a zewnętrzną stroną membrany
V = 60;
% bramka typu 'm'
m = 0.2;
% bramka typu 'n'
n = 0.3;
% bramka typu 'h'
h = 0.2;
% wektor czasu
t = 0:0.0001:10;
% wektor p składający się z czterech elementów: V, m, n oraz h
p=[V;m;n;h];
% funkcja do rowiązywania równa... |
function []=Write_vtk_point(Pts,Normals,filename,Scalar)
% Usage:
% Write_vtk_surface(Pts, Tri, Normals, Scalars, LUT, filename);
fid = fopen(filename, 'w');
fprintf(fid, '# vtk DataFile Version 3.0\nvtk output\nASCII\n');
fprintf(fid, 'DATASET POLYDATA\n');
fprintf(fid, 'POINTS %d float\n',size(Pts,... |
function [solver, a] = rule_lab2_1( class1, class2, pr)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
M1 = mean(class1);
M2 = mean(class2);
n1 = length(class1);
n2 = length(class2);
err1=0;
err2=0;
err1_2=0;
err2_2=0;
err1_3=0;
err2_3=0;
S1 = cov(class1);
S2 = cov(class2);
AS1 = inv(S1);... |
clear;clc;close all
SamFreq=5120;
N=5*SamFreq;
fs=SamFreq;
t=0:1/fs:(N-1)/fs;
s_f1=(2.5*t.^2+2*t);s_f2=(25*t.^2+20*t);
f1=5*t+2;f2=20+50*t;
f1_zheng=f1;f2_zheng=f2;
figure(1);
plot(t,f1,'r');hold on;plot(t,f2,'b');
sig=cos(2*pi*s_f1)+sin(2*pi*s_f2); %另别的sig
%sig=cos(2*pi*(10*t.^2+2*t))+cos(2*pi*(20*t.^2+4*t)); %另别的sig... |
% md5
% Halla el resumen MD5 del mensaje, como una cadena hexadecimal.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% PASO 1.- INTRODUCIMOS VARIABLES Y CONSTANTES NECESARIAS
clc
%PASO 1.1.- ESCRIBIMOS EL MENSAJE
mensaje= input('Introduce el mensaje entre comillas:');
while(~ischar(mens... |
% This defines a data structure that describes the physical state of a
% superconducting material for a given range of positions and energies.
% This class inherits the internal structure of the 'Metal' class.
%
% Written by Jabir Ali Ouassou <jabirali@switzerlandmail.ch>
% Inspired by a similar program written by Sol ... |
% weighting
function [gen, weight_a, weight_b] = fusion_strategy(features_a, features_b, source_a, source_b)
[m1,n1] = size(source_a);
% resize
resize_temp1 = imresize(features_a, [m1, n1]);
resize_temp2 = imresize(features_b, [m1, n1]);
% soft-max
weight_ave_temp1 = resize_temp1./(resize_temp1+resize_temp2);
weight_a... |
function [G,abitazione,indirizzo,vincoli]=inserisci_nodo(G,abitazione,indirizzo,vincoli) % inserisci_nodo: l'utente può aggiungere un nodo al grafo iniziale
n=G.get_size();
m=n;
while m==n ... |
% speccos.m plot the spectrum of a cosine wave
f1=50; phi=0; % specify frequency and phase
f2=150;
f3 = 250
time=2; % length of time
Ts=1/1000; % time interval between samples
t=Ts:Ts:time; % create a time vector
x=cos(2*pi*f1*t+phi) + cos(2*pi*f2*t+phi... |
%This file is used to test dilation.
A = imread('wirebondmask.tif')
temp = IPdilate('wirebondmask.tif', [1 1 1; 1 1 1; 1 1 1])
figure;
subplot(121);
colormap(gray(256));
imagesc(A);
axis equal;
axis tight;
title('INPUT IMAGE')
subplot(122);
colormap(gray(256));
imagesc(temp);
axis equal;
axis tight;... |
function loop_test3()
err = 1;
for i = 1:10
err = 0;
for l = 2:10,
for k = 2:10,
if (err <= abs(pi))
err = abs(pi);
end;
end;
err;
end;
err;
end;
err; |
function [a] = commondivisor(a,b)
while(b)
t=mod(a,b);
a=b;
b=t;
end
end |
function PixelSize=as_improc_pixelsize(scale)
if ~exist('scale','var')
scale=inputdlg('length of the bar in Ám');
if ~isempty(scale)
scale=str2double(scale{1}); %Ám : scale of the bar that appears in your image
end
end
if ~isempty(scale) && ~isnan(scale)
h=imline;
PixelSize=scale/length(find... |
function varargout = Edge_Detection(varargin)
% EDGE_DETECTION MATLAB code for Edge_Detection.fig
% EDGE_DETECTION, by itself, creates a new EDGE_DETECTION or raises the existing
% singleton*.
%
% H = EDGE_DETECTION returns the handle to a new EDGE_DETECTION or the handle to
% the existing singleton... |
load('npfda_pho_norm.mat');
% Normalization
x_timegrid = phoX';
sample_mean = mean(mean(phoY));
sample_std = 2*std(phoY(:));
phoY = phoY - sample_mean;
phoY = phoY / sample_std;
hyper = make_hyper();
prior = nhgpprior(x_timegrid, ...
hyper.mu_m, hyper.G_m, hyper.L_m, ...
... |
obj = analysis.void_finder;
obj.loadExpt(2);
obj.loadAndFilterStream(1,1);
data = obj.filtered_cur_stream_data;
d1 = data.dif2;
d2 = d1.dif2;
figure
plot(data)
yyaxis right
plot(d2)
threshold = 3*10^-8;
d = d2.d;
[pks,locs] = findpeaks(d,'MinPeakHeight',threshold);
tic
dd = -d;
[mins,m_locs] = findpeaks(dd,'MinPeakH... |
function Phasemovie
tmax=20;
x=-5:0.5:5;
y=-3:0.2:3;
axis([-7,7,-4,4]);
hold on
xlabel('x')
ylabel('y')
plot(0,0,'m*',-pi,0,'m*',pi,0,'m*')
[X,Y]=meshgrid(x,y);
P=Y;
Q=sin(X+Y);
D=sqrt(P.^2+Q.^2);
quiver(X,Y,P./D,Q./D,0.5,'k')
[x0,y0]=ginput(1);
[T,Y]=ode45(@ff,[0,tmax],[x0; y0]);% ili s ... |
function [classifier, parameters,ROC_values] = as_axonSeg_make_DA_classifier(axonSeg_step1,axonSeg_segCorrected,axonSeg_gray, parameters,type,val)
% OUTPUTS -----------------------------------------------------------------
% Rejected_axons_img (OUT) : binary image of rejected axons
% Accepted_axons_img (OUT) : binary i... |
% Cs Ax2 and Na 'x' Scan
%% load
d = replot2([20180116, 213631]);
ParamsNa = [linspace(18.04, 18.26, 18), linspace(18.98, 19.24, 14), ...
linspace(19.48, 19.74, 18)] * 1e6;
ParamsCs = linspace(-180, 250, 50) * 1e3; % Ax2,3 Full
%% Cs
i=1; %which scan?
m=2; %which survival?
SurvProb = d(i).Analysis.SurvivalPro... |
%% Finite Difference BOUNDARY Honeycomb Spectra
clear
%% set grid size
a = 1;
mx = 200/(1*a);
%% set up honeycomb lattice
q = 4*pi/(a*sqrt(3));
k1 = q*[1;sqrt(3)]/2;
k2 = q*[1;-sqrt(3)]/2;
k3 = k1+k2;
v11 = sqrt(3)/2; v12 = sqrt(3)/2;
v21 = 1/2; v22 = -1/2;
%% different edges
ktilde = k2;
%% quasimomentum vectors
... |
function options = sgplvmFOLSOptions(type)
% SGPLVMFOLSOPTIONS Returns options struct for fols model
% FORMAT
% DESC Return a options struct for the fols model
% ARG type : options specifier
% RETURN options : fols option struct
%
% SEEALSO : sgplvmCreate
%
% COPYRIGHT : Neil D. Lawrence, Carl Henrik Ek, Mathieu Salzm... |
clc;
clear all;
close all;
x=[0 0 1 1;0 1 0 1];
t=[0 1 1 1];
x1=x(:,1);x2=x(:,2);x3=x(:,3);x4=x(:,4);
t1=t(1);t2=t(2);t3=t(3);t4=t(4);
w1=[0.5 0.5]
b1=0.1
eta=1;
e=1;eteration=0;
while(e~=0)
a1=hardlim(w1*x1+b1);
e1=t1-a1;
if e1~=0
w2=w1+eta*e1*x1';
b2=b1+e1;
else
w2=w1;
... |
%% Script for debugging CLEAN
close;
dynamic_range = 12; % dB
xmin = -.25; xmax = .25;
ymin = -.25; ymax = .25;
xmin = -1.5; xmax = 1.5;
ymin = -2; ymax = .5;
Pimp = P;
Pimp(real(Pimp)<0) = 0;
SPLint = 20*log10(sqrt(real(reshape(Pimp, N_X, N_Y).'))/2e-5);
maxval = ceil(max(real(SPLint(:))));
minval = maxval - dynamic... |
function test_hybrid_simulation
% number of states
Nq = 5; Nv = 5;
q_idx = 1:Nq;
v_idx = Nq+1:Nq+Nv;
% initialize states and parameters
q0 = zeros(Nq,1);
q0(3) = pi/8;
q0(2) = 2.5;
v0 = zeros(Nv,1);
x0 = [q0;v0];
p = example_parameters;
p_array = param2array(p);
... |
function [np] = ppmv2np(ppmv,d,scatteringVolume)
%-------------------------------------------------------------------------------
% Version 20180101, Silviu Rei
% function [np] = ppmv2np(ppmv,d,scatteringVolume)
% The function returns the number of partices in the scattering volume
% based on volume concentration inp... |
function dydt = pknmm(time,ini)
C1 = ini(1);
C2 = ini(2);
C3 = ini(3);
Ceff = ini(4);
g = ini(5);
weight = ini(6);
height= ini(7);
age = ini(8);
% concentration variance equations
if g==2
lbm = 1.1*(weight) - 128*(weight/height)^2;
else
lbm = 1.07*weight - 148*(weight/height)^2;
end
V1 =... |
function saveSubjectInfo(trialinfo,const,subject)
% save subject information
nameOut=['data/' const.code '.mat'];
if exist(nameOut,'file')
name=dir(['data/' const.code '.mat']);
nameOut2=['data/' const.code '_' date '.mat'];
copyfile(nameOut,nameOut2);
end
save(nameOut,'const','trialinfo','subject');
|
%function ImageClassification
folder_path1 = './cs558s18_hw4/ImClass/';
%get the histogram
bins = 8;
train_label = zeros(12,1);
train_data = zeros(12,bins*3);
test_label = zeros(12,1);
test_data = zeros(12,bins*3);
classes_filenames = {'coast', 'forest', 'insidecity'};
count = 1;
k=11;
%get the datasets
f... |
function [ commonDataInfo, aggregationInfo ] = firstguess_fillcomputesol(commonDataInfo,refInfo, aggregationInfo,periodIndex,aqiIndex)
fName=strtrim(commonDataInfo.pathANN(periodIndex).ANNs(aqiIndex,:));
aggregationInfo.extraInfo=0;
if (strcmp(fName,'-999') == 0)
[alpha, omega, radius, flatWeight, pollutantList]=f... |
function [CO_no_UT,UT_ind]=find_UT_ind(general_behavior_data_file_name,behav_params_file_name,CO_ind)
load(general_behavior_data_file_name)
load(behav_params_file_name)
% U-turns are defined like CO that one of the bat changed his direction X
% meters after CO
%1. find ind that bats change directions (vel ... |
clc;
clear all
close all;
load('BAT_data.mat');
% %% Find the Charge, Discharge and Idle States
% % Add a state of the battery
%
% i = -1 * i;
%
% SoC(:,2) = 0; %% add initially all state is zero
%
% for time_index = 1:length(t_vec)-1
%
% if( i(time_index) > 0 ) % battery is discharging
% So... |
classdef Market < Estimate
% MARKET Calculates market equilibrium
% Based on ownership structure and conduct.
properties
firm
p %prices
c %Costs
gamma = 0 % Scale effects
demand % Demand class
marketid % Protected?
end
prope... |
function Ei400_uvw100_at110auto(varargin)
data_source= fullfile(pwd,'Data','Fe_ei401.sqw');
avrg_par=[0,0,1139.482];
no_chkpnts= 'True';
Imax = 1; % fitting considered wrong if intensity deviates from average by this range
if nargin == 0
repPoints1= [-0.3375,-0.175,0,0.175,0.375;
135,30,0,30,190];
... |
function write_alarms_ffb
% function write_alarms_ffb
%
% This routine writes the corrector magnet and IDBPM safety trip points, which are used
% by the fast feedback system.
%
% Christoph Steier, August 2002
%
% 6-19-06 T.Scarvie, modified to work with new Middle Layer
%
% Eric's routines seem to work differently than... |
% Copyright (c) 2017 Zi Wang
function K = compute_gram(xx, hyp, hyp_idx, z)
% This function computes the gram matrix for an add-GP.
all_cat = unique(z);
K = 0;
for i = 1:length(all_cat)
K = K + computeKmm(xx(:,z==all_cat(i)), hyp.l(hyp_idx, z==all_cat(i))', ...
hyp.sigma(hyp_idx, all_cat(i)), hyp.sigma0(hyp... |
% qhist1 Quick histogram calculation for 1D values
%
% This function quickly calculates histogram values for a uniformly spaced
% grid.
% weight=qhist1(value,bin);
% NOTE: this function does generate histogram plots! To display the
% results, use the plot or bar function.
% plot(bin,weight);
% bar(bin,weight,1);... |
% Estimates the homography H such that H * x = b. Performs RANSAC iterations
% times. Returns H along with the number of inliers and its total score (the
% amount of error; lower is better).
function [best_H, best_num_inliers, best_total_score] = estimate_homography(x, b, iterations)
threshold = 5;
best_num_inliers... |
clear all;
N=10; %number of neurons per population
numCluster=5; % number of populations
k_intraCluster=1; %connections strenght within cluster
delay_intraClust=0.1; %connections delays within cluster
k_interCluster=1; %connections strenght between cluster
delay_interClust=0.3; %connections delays between cluster
k... |
% bayermask provides sampled bayer CFA data and bayer mask
%
% [bayer mask] = bayermask(data,pattern)
%
%
%Output parameter:
% bayer: bayer data. Zero is set for non-observed pixel.
% mask: One is set for observed pixel and zero is set for non-observed pixel.
%
%
%Input parameter:
% data: rgb full color imag... |
function loadlayerprofile(varargin)
%*************************************************
%DATE: 10/8/2007 (created); 10/8/2007 (modified)
%FUNCTION: load layer profiles
%INPUTS: NULL
%OUTPUTS: NULL
%muwn.gu@gmail.com
%*************************************************
global Layerprofile
Layerprofile.color.sil... |
function savecal(tag,varargin)
%
% savecal(tag,type,val,...)
% Add calibration data to a correctly-named file in the
% cal directory on the tag path. The data type is a
% string selected from the following:
% 'AUTHOR' - string containing the initials or name of creator
% 'CAL' - structure of ca... |
% function [mBestImage, mBestMembership, bestObjVal, bestMatApproxVal, idealEucObjVal, idealManhObjVal, runningTime, totalIterNum] = runBMAlgor(mAdj,...
% sObj, sAlgor, posNum, convEpsilon, runNum, sDist, sPosAlgor, bDiscretiseMembership, bColNormalise, varargin)
function [mBestImage, mBestMembership, bestObjVal, c... |
% in the same units as the spectrum),
% the forth row is the mask array.
%
% The spectra are binned log-linear. Units are 10^(-17) erg/cm^2/s/Ang
% http://classic.sdss.org/dr7/products/spectra/read_spSpec.html
% Notice that the wavelength vector is not contained in the image,
% but must be generated from parameters in ... |
function status = s88x_waitForCommandSent(timeout)
%s88x_waitForCommandSent: waits for the last non-query command sent to be
%completed. -Adam C. Snyder adam@adamcsnyder.com
if nargin<1, timeout=10; end;
[~,status] = s88x_dataStatus;
cmdCompleted = bitget(status(1),2)==1;
th=tic;
while ~cmdCompleted&&toc(th)<tim... |
function [commandc] = feat_HCLV_Photo_7T(outFile,funcVol,anatVol,EVs,WA)
% Write a .fsf file for first-level feat for the HCLV_Photo_7T protocol
%
% Usage:
% feat_HCLV_Photo_7T(outFile,funcVol,anatVol,EVs,WA)
%
% Inputs:
% outFile = name of output .fsf file (fullpath)
% funcVol = name of input functi... |
function S = predict_list_linear_regression( test_data, beta_list, mode )
% test_data is in common format
% beta_list is length B cell array. beta_list{i} is [d,1]
%
% S is [N,B]
B = length(beta_list);
N = length(test_data);
S = zeros(N,B);
for k = 1:B
features = conseqopt_features(test_data,S(:,1:k-1),mode);
for i... |
clear
clc
source_file1 = 'C:\Temp\Oscop data\result_No.mat';
source_file2 = 'C:\Temp\Oscop data\result_ga.mat';
dest_dir = 'C:\Temp\Oscop data\';
load(source_file1,'No');
for i = 1:length(No)
a=No{i,5}(1:120)
end
load(source_file1,'ga');
for i = 1:length(ga)
b=No{i,5}(1:120)
end |
function [M,G] = perform_geodesic_interpolation(W,points,f,options)
% perform_geodesic_interpolation - interpolate function values
%
% [M,G] = perform_geodesic_interpolation(W,points,f,options);
%
% f(:,i) is the value of the function at the point points(:,i).
%
% options.method can be 'powerlaw' or 'gaussian'.
... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2010 - 2015 Moon Express, Inc.
% All Rights Reserved.
%
% PROPRIETARY DATA NOTICE:
% The data herein include Proprietary Data and are restricted under the
% Data Rights provisions of Lunar CATALYST Space Act Agreement
% No. SAAM ID#... |
% SWAPMODEL returns a structure for a three-component model
% with guesses and swaps. Based on Bays, Catalao, & Husain (2009) model.
% This is an extension of the StandardMixtureModel that allows for
% observers' misreporting incorrect items.
%
% In addition to data.errors, the data struct should include:
% data.dist... |
function [Hd,g] = filter1
%FILTER1_1 Returns a discrete-time filter object.
% Author: ECE486 Spring 2015 Lab Group 2
% Author: Jacob Allenwood, Travis Russell, Jeremiah Simonsen
%
% This function generates a low-pass filter for the purpose of filtering
% the samples input waveform for the FSK demodulator developed for ... |
function [m, s] = henry (x, nb, k)
%
% For reference, look for:
% - Q-Q plot (droite de henry in french) qqplot.m
% - P-P plot ppplot.m
% - normal probability plot
%
% For normality test, use skewness and kurtosis (both should be tiny)
% - D'Agostino's K^2 test
% - Jarque-Bera test
% or by comparing dat... |
% Stability analysis
n=-5:1:5;
x1=n;
y1=n.*x1;
subplot(4,1,1)
stem(n,y1,'g--s');
title('1.4(f)-1');
xlabel('x_1[n]=n');
ylabel('y_1[n]=nx_1[n]');
% invertibility and time-invariant analysis
x2=[zeros(1,5) 1 zeros(1,5)];
x3=3 .* x2
y2=n .* x2;
y3=n .* x3;
y4=(n+1) .* x2;
subplot(4,1,2);
stem(n,y2,'r--h');
title('1.4(... |
function [sys,x0,str,ts] = scrqp(t,x,u,flag,T0,nr,nq,np)
% FBFW feedforward feedback controller
% Output of the controller is calculated follows:
%
% R(z^-1) Q(z^-1)
% U(z^-1) = ---------- * W(z^-1) - --------- * Y(z^-1)
% P(z^-1) P(z^-1)
%
% Ord... |
function lik = q4_likelihood(mu, m, H)
% Returns the likelihood for different values of mu, given the scalar parameters m and H.
%
% INPUT
% mu: [1 x N] vector, containing N different values for mu
% m: scalar
% H: scalar
%
% OUTPUT
% lik: [1 x N] vector containing the likelihood values associated with the entries ... |
%%Pràctica 1 Fonaments de Comunicació 1
%% Apartat A
w0=4*pi;
T=2*pi/w0;
u = inline('t>=0')
t=-4*T:T/100:4*T;
x1=3*u(t-0.5).*cos(4*pi*t+pi/3) ;
plot(t,x1)
axis([-4*T 4*T -5 5]);
title('Señal 1a');
grid;
xlabel('Tiempo (segundos)');
ylabel('x1(t)');
%%
%Apartat b
%% Apartat A
w0=4*pi;
T=2*pi/w0;
u = inline('t>=0'... |
% Gregor Barth (GRBH), Jan Draegert (JADT), Ercan Kücükkaraca (ERKA)
#used octave packages: control, general, image, signal, sockets, specfun
function aufgabe4()
pkg load all;
#variables
clc;
#set all variables here
#(max_L) *(k_Lx k_Ly) * (x) (b_L)
#(max_H) (k_Hx k_Hy) (y) (b_H)
global k_Lx; globa... |
function corrected = correctOdometry(nr)
global odometry
global last_correction_y
last_correction_y = 0;
global last_correction_x
last_correction_x = 0;
global corr_x
global corr_y
if nr <= 12
x = odometry(1)-corr_x;
y = odometry(2)+corr_y;
elseif nr <= 21
x = odometry(1) - corr_x;
y = odometry(2) + co... |
Pic=imread('IMG.jpg');
%%%%
% a) grayscale
a=rgb2gray(Pic);
figure;
subplot(3,2,1);
imshow(a);
title('a) Grayscale image');
%b) negative image
b=imcomplement(Pic);
subplot(3,2,2);
imshow(b);
title('b) Negative image');
%c) mirror image
% http://www.mathworks.com/help/matlab/ref/flipdim.html?searchH... |
% Split data into TRAINING SET and UNSEEN DATASET , permutation dataset and
% classes
%This script is for datasets with 18 features
function [TRAININGSET, UNSEENDATA, UNSEENCLASSES, PERMUDATA, PERMCLASS] = firstsplit(data)
classes = data(:,19); %choose the classes row
actualdata = data(:, 1:18); % choose all data o... |
function create_job_shell(outDir,job_name,matlab_string)
% Writes out a shell script to run matlab code on the cluster.
%
% Usage:
% create_job_shell(outDir,job_name,matlab_string)
%
% example:
% outDir = '~/cluster_scripts';
% job_name = 'job_example';
% matlab_string = 'sort_nifti(''~/data/session_dir'')... |
function C = generate_candidates (L)
C = {};
k = 1;
for i = 1 : length(L) - 1
for j = i + 1 : length(L)
if L{i}(length(L{i})) ~= L{j}(length(L{j})) && length(setdiff(L{i}, L{j})) == 1
C{k} = union(L{i}, L{j});
k = k + 1;
end
end
end
return
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%master.m (the first script that you would call when you start analysing
%%USEFUL OUTPUT VARIABLES
%%cell_rok is the structure containing all the relevant informatio... |
function [eff,X, SR_new, SR_oud, rho_n, z] = efficient2(input)
% Computes the Prior year efficient returns and Sharpe ratio improvements
av12lag = zeros(1,length(input));
for i = 2:length(input)
%if i < 13
if i > 12
% av12lag(i) = mean(input(1:i-1));
%else
av12lag(i) = sum(input(i-12:... |
%% Various criterion to consider:
% 1. Repeatability of peak position
% 2. Repeatability of peak rate
% 3. Min peak firing rate
% 4. Dymamic modulation range (max-min)/mean
% 5. Spatial information (calculate)
% 6. Range of peak
llim = 00;
hlim = 200;
peakPosVarLim = 200;
peakVarLim = 2; % peak > mean + peakVarLim*(std... |
function plot_med_coal_blend_egrid(boot_cq_TE, subrgn)
%% do the following
% distribution of each plant
% find the median, min, max, 25th %, and 75th %
% sort by medians with plant info and the above percentiles
% plot cdf
% plot 25th and 75th distributions in the same manner, use triangle for
% 25th, square for 75t... |
function [c,ceq] = TYpowerConstraints_AS_GlobalOnly(x,currentConstraints,pulseTR,sinc_pulse)
ceq = [];
% c<=0
% ceq=0
% See https://uk.mathworks.com/help/optim/ug/nonlinear-constraints.html for
% the form of g and geq
% x is the vector of optimisation parameters (typically RF mag, RF phase, gradient??)
% currentConstr... |
function accuracy=evaluateMP(Test_adjusted,Testlabel,priorVector,meanMatrix,stdMatrix,lambdaMatrix)
n=0;
for i=1:length(Test_adjusted)
labelpredict=labelMP(Test_adjusted(i,:),meanMatrix,stdMatrix,lambdaMatrix,priorVector);
if labelpredict==Testlabel(i)
n=n+1;
end
end
accuracy=n/length(Test_adj... |
function [breath_cycle] = nb_cycles_respiration(convoluted_signal, order, durationVideo)
%Suite à la convolution du signal (using FFT & LowPass Filter)
%%%%%%%%%%%%%%%%%%%%%%%Compteur du nombre de cycles respiratoires%%%%%%%%%%%%%
dcon=diff(convoluted_signal); %dérivée du signal filtré (entré en paramètre)
ch... |
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