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%% TANGLEANALYSIS.m
% This analysis determines how 'tangled' a given dataset is. That is, how
% often the projections in high D space cross over each other in different
% directions. The tangle index of two time points is given by the squared
% difference in derivative divided by the squared difference in state at
% t... |
DataOriginal = runData.original;
h1 = figure();
subplot(3,1,1)
histfit(runData.original.rt)
title('RT cue-reach start')
subplot(3,1,2)
histfit(runData.original.reach)
title('Reach Time')
subplot(3,1,3)
title('Return Time')
histfit(runData.original.return)
if saveProcess
str = 'RT_phases';
saveas(h1,[f... |
clear;
clc;
load('dvrk_mtm_psm.mat');
%% the configuration of PSM
syms s1 s2 s3 s4 s5 s6 s7;
DOF = 7;
mtm_config = [% type a alpha d theta
'r' 0 0 0 s1+pi/2;...
'r' 0 pi/2 0 s2-pi/2;...
'r' -0.2794 ... |
function [opts] = opt_init()
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
opts = [];
if ~isfield(opts,'mu') opts.mu=20; end %% regularization term scale
if ~isfield(opts,'delta') opts.delta=1; end %% delta<||A^*A||, since A here is a subsampled Fourier matrix, could be fixe... |
clc;clear;
addpath('../functions')
addpath('../functions/l1_ls_matlab')
addpath('../data')
% Mosek setup
% javaaddpath('C:\Program Files\Mosek\8\tools\platform\win64x86\bin/mosekmatlab.jar')
% addpath('C:\Program Files\Mosek\8\toolbox\r2014a')
addpath ~/mosek/8/toolbox/r2014a
% Read in data & some general setup
file_n... |
%fprintf('%15s %6i %10i %10i %10i\n', 'n=',5,10,20,90)
for e=1:5
es = [1 0.5 0 -0.5 -1];
eps = 10^(es(e));
P = rand(100);
eigs = rand(100, 1)*3
for i =1:100
if(eigs(i) < 1)
eigs(i) = 4 + (eigs(i) - 0.5)*eps;
elseif(eigs(i) < 2)
eigs(i) = 5 + ... |
function varargout = loc_laser_left(varargin)
% loc_laser_left M-file for loc_laser_left.fig
% loc_laser_left, by itself, creates a new loc_laser_left or raises the existing
% singleton*.
%
% H = loc_laser_left returns the handle to a new loc_laser_left or the handle to
% the existing singleton*.
%
... |
function OUTctf = ctFIRE_1(imgName,imgPath)
% ctFIRE to process one image each time
% image
% Input:
% imgName: name of the image to be processed
% imgPath: path of the image to be processed
% Output:
% OUTctf: a structure containing the extracted fiber information
% with options to process the original as we... |
function prob_048
% The series,
%
% 1^1 + 2^2 + 3^3 + ... + 10^10 = 10405071317.
%
% Find the last ten digits of the series,
%
% 1^1 + 2^2 + 3^3 + ... + 1000^1000.
%
%
% A: 9110846700
%
nDigits = 10;
base = 10^nDigits;
% Index of last summand
N = 1000;
val = 0;
for i = 1:N
val = val + pow_a_b_mod_n(i... |
%%%%%%% Lab 6 DSP - Test Phaser
close all; clear; clc;
%%%%% 0. Importación de señal
file1 = 'soplo_rodrigo.wav';
file2 = 'soplo_rodrigo_phaser.wav';
[data1, fs1] = audioread(file1);
[data2, fs2] = audioread(file2);
%%%%% 1. Parámetros
%%% Muestreo
T_spect = 0.05;
%%%%% 2. Obtención de espectrogramas
figure
spectr... |
function [coeffs,LegPoly] = expand_Legendre(x,f,N)
% This function expands f(x), on range -1<=x<=1 on the basis of the first N
% Legendre-polynomials, and returns the expansion coefficients and the polynomials.
x=map2colvec(x);
f=map2colvec(f);
dx=[diff(x); (max(x)-min(x))/length(x)];
for ind1=1:N
temp = leg... |
% calculate rate of OH + 12C2H2Cl2 -> products
% Updated 6/10/15
% Based on MCM v. 3.3
% rate = kOH12C2H2Cl2(T,M)
% 1-2-Dichloroethane, 1-2-DCE
function j = kOH12C2H2Cl2(T,M)
j = 1.94e-12.*exp(90../T); |
clf
fc = 6
down = 3
up = 6
N = 30 % number of sinusoid wave
t = 0:0.01:(N)/(2*pi)
origin_signal = cos(2*pi*fc*t)
load('./filter/FIR_LP')
load('./filter/IIR_LP')
% up and down sample signal
up_sampling_signal = DAC(origin_signal,up)
down_then_up_signal = DAC(ADC(origin_signal,up),up)
% filter the signal
[h,w] = freqz(... |
function rf = vigraImporthdf5RF( filename, groupname);
% function rf = vigraImporthdf5RF( filename, groupname);
%
% Import a previously trained Random Forest from a hdf5 file
%
% rf - MATLAB cell array representing the random forest classifier
% filename - name of hdf5 file
%
% groupname - opti... |
figure(414);
subplot(2,1,2);
plot(IRDB.abfil_ft, abfil_fpspec_simdata(:, 1),...
'-x','MarkerIndices' , peak.idx(1: peak.ctr(1), 1),...
'MarkerSize', 15, 'MarkerEdgeColor', 'red');
title('(b)');
xlabel('Frequency');
ylabel('Amplitude'); |
%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Sam Feig
% Vladimir Zhdanov
%
% CSCI 4831/5722
% Homework 4
% Instructor: Ioana Fleming
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [outImg] = detectOutliers(D_LR, D_RL, T_LR)
[m, n] = size(D_LR);
outImg = zeros(m, n);
for i = 1:m
for j = 1:n
% If outl... |
% Multi-graph manifold alignment for RGB image visualization.
% Neighbourhood preserving projections
% Sparcity preserving projections
% Locality preserving projections
%%
bandsList = [10, 18, 26, 35, 51, 56,70, 75, 87, 99];
% bandsList = [120, 126, 135, 151, 156, 170, 175, 187, 199];
reduceImage = Reduce... |
%[s_read_REF] read, save and show REF data in LIST/DATA format.
%
%
% Last modified
% 2010.07.26.
% Change psi to PSI to remove a conflict with Matlab function 'psi()'.
% 2010.08.09.
% This is generated from [REF_readsaveshow.m]. This only contains the
% last comment from the file.
% 2010.08.18.
% ... |
function pValue = hotellingModified(bin,time1,time2)
[iInd, jInd] = find(bin.uVar(:,:,time1)~=0 &...
bin.uVar(:,:,time2)~=0);
T2=zeros(length(bin.x),length(bin.y));
nu=zeros(length(bin.x),length(bin.y));
for m=1:length(iInd)
S1=zeros(2,2);
S1(1,1)=bin.uVar(iInd(m),jInd(m),time1);
S1(2,2)=bin... |
function [Sv] = SkewSymm(v)
%UNTITLED8 Summary of this function goes here
% Detailed explanation goes here
v1 = v(1,1);
v2 = v(1,2);
v3 = v(1,3);
Sv = [0 -v3 v2; v3 0 -v1;-v2 v1 0];
end
|
function SunRef = Task3_SunPointingFrame
SunRef.RN = Euler1232C([pi/2 0 0]')*Euler1232C([0 0 pi]');
SunRef.omega = [0 0 0]';
end |
% TEST_POROV
% Testuje parametre zadaneho modelu v POROVNAT
% Ak su zadane parametre v poriadku, spusti sa POROVNAT2
% Copyright is with the following author(s):
%
% (c) 2012 Juraj Oravec, Slovak University of Technology in Bratislava,
% juraj.oravec@stuba.sk
% (c) 2012 Monika Bakosova, Slovak University of Technology... |
function [x,fx,ef,numit] = gennewton(f,x,cc,varargin)
% input arguments: f function handle
% x starting values
% cc convergence criteria
% varargin either empty or string 'Newton' or 'Broyden'
%% get conver... |
% 03_确定最优特征
clearvars -except FC Important_fc FC_Important
% 1）初始化变量，前55个被试为PD，用-1来表示，后50个被试为NC，用+1来进行表示
PD = -ones(1, 55);
NC = ones(1, 50);
labels = [PD, NC];
n = 65; % 划分的个数分别是：35:30:40；将前75个作为训练集+验证集；
% 最后40个作为测试集
% 2）随机抽取样本的过程如下所示：
% 打乱所有被试的编号
x = randperm(105);
y = x(1:n); ... |
function [eigVecs,eigVals] = ...
DispEigCalcIsoSS(DiffMobObj,GridObj,ParamObj,Interactions,Diffusion,...
SparseMat,kxHolder,kyHolder)
% Vectors are column vectors
Nm = ParamObj.Nm;
% Prefactors
DiagPreFac = -( DiffMobObj.D_par + DiffMobObj.D_perp) / 2 .* ...
( GridObj.kx(kxHolder) .^ 2 + GridObj.ky(kyHold... |
clear; clc;
global HAND;
global threshold;
threshold = 10;
delta = 8;
dr = 0.5;
dh = -1;
hi = 315.05;
ri = -12.675;
% dr = -0.5;
% dh = 1;
% hi = 90.05;
% ri = 99.825;
opengl software
hvec = hi:dh:HAND;%315.05
rvec = ri:dr:(ri+(length(hvec)-1)*dr);
% for i = 1:length(rvec)
% [a, b, thetavec(i)] = findLimit(ri,h... |
function sig = genSpikeSignal(m,n)
% generate spike signal
sig = zeros(n,1);
ids = randperm(n,m);
val = randi(2,m,1)-1.5 ;
sig(ids) = val*2;
|
function v4 = rule4(n,boid,pred,zop,fov)
% RULE4: function that calculates the effect of Rule 4: boids try to avoid
% a possible incoming predator
%
% INPUTS:
% n = number of boids
% boids = boids position and velocity
% pred = current predator position and velocity
% zop = (circular) zone of predator avoidance
... |
%PLC_EEG_Analyzer3.m
%Created by YY, 1/22/15
%% Extract ERPs
%Sub 48 52 (updated 2/8/15; old rej: 16,48,49,52) be removed from further EEG analysis due to too many
%movements and preculiar extraneous experimental conditions (ie. refusal to
%use chin rest, physiological symptoms during experiment, no contignency
%retai... |
function x = unitstep(t)
% -- unitstep (t)
% unit step function (heaviside function)
%
% if t >= 0 returns 1 otherwise 0.
%
if t < 0
x = 0
else
x = 1
end
end
|
function Check = checkRules(rules)
N = length(rules);
Check = zeros(N,1);
for i = 1:N
if isempty(rules{i})
Check(i) = 0;
else
t = strtrim(char(rules{i}));
AND = strfind(t,'and');
OR = strfind(t,'or');
if length(AND) + length(OR) == 0
Check(i) = 1;... |
function u = ctrlGetOutOfTheWay(~,z,xi,wn,P)
% This controller attempts to actively move the motor out of the way,
% preventing oscillations and allowing nearly free swinging of the pendulum
qf = z(1,:);
qm = z(2,:);
dqf = z(3,:);
dqm = z(4,:);
Jm = P.Jm; % Motor inertia
Ks = P.Ks; %Spring constant
u = (Jm*wn*wn... |
clear all;
brick = ConnectBrick('EV3PP');
brick.beep();
global key
InitKeyboard();
brick.ResetMotorAngle('C');
while true
pause(0.01);
switch key
case 'uparrow'
disp('forward');
forward(brick);
case 'downarrow'
disp('backward');
... |
% Ograniczenia
du_max = 0.1;
u_min = 0.6;
u_max = 1.6;
% Punkt pracy
u_pp = 1.1;
y_pp = 2.5;
% Nastawy
D = 200;
N = 32;
Nu = 3;
lambda = 1;
% Macierz M
M = zeros(N,Nu);
for i = 1:size(M,1)
for j = 1:size(M,2)
if i>=j
M(i,j) = s(i-j+1);
end
end
end
% Macierz Mp
Mp = zeros(N,D-1);
for ... |
clc;
clear;
x=input('Enter the first sequence: ');
y=input('Enter the second sequence: ');
display(' ');
display(' Convolution with function:');
convolution_ans1=conv(x,y)
lx=length(x);
ly=length(y);
con_l=lx+ly-1;
x=[x zeros(1,con_l-lx)];
y=[y zeros(1,con_l-ly)];
for i=1:con_l
... |
%% For reproducing Figure 6a-c combined subject data
clear; close all;
inits = {'Subject1','Subject2','Subject3'};
figure(1); clf;
purple = [0.5961 0.3059 0.6392];
% load data
allTrials = table;
for ini=1:length(inits)
load(['data/' inits{ini}]);
allTrials = [allTrials; trials];
end
D = unique(trials.Di... |
% PROFILE - Profiles the performance of calculating sliding window correlations between large data sets.
%
% After writing the simple correlation function MEXCORRELATE in C earlier today, I decided it wouldn't require much more
% effort to just write the whole sliding window algorithm in C for even greater efficien... |
Nvoxels = 50;
NSub = 100;
X = round(rand(NSub,1));
a = 0.5;
M = a.*repmat(X,1,Nvoxels) + randn(NSub,Nvoxels);
b = 0.5;
cP = 0.5;
Y = cP.*X + b.*M(:,4) + randn(NSub,1);
corr([X M Y]);
BaseDir = '/home/steffejr/Scripts/TestThimgs';
data = {};
data{1} = X;
data{2} = M;
data{3} = Y;
% Create a structure of corresponding... |
function output = DeZigZag8x8(img)
%DEZIGZAG8X8 Summary of this function goes here
% Detailed explanation goes here
ZigZag = [1 2 6 7 15 16 28 29;
3 5 8 14 17 27 30 43;
4 9 13 18 26 31 42 44;
10 12 19 25 32 41 45 54;
11 20 24 33 40 46 53 55;
21 23 34 39 47 52... |
f = @(x) (1./(1+2.*x)) - ((1-x)./(1+x));
g = @(x) (2.*(x.^2))./((1+x).*(1+(2.*x))); %simplified version
x = 2:1e-6:2.1;
y = -1e-6:1e-10:1e-6;
figure(1);
plot(f(x));
figure(2);
plot(f(y));
figure(3);
plot(g(y)); |
% Compute the error of a pose-landmark constraint
% x 3x1 vector (x,y,theta) of the robot pose
% l 2x1 vector (x,y) of the landmark
% z 2x1 vector (x,y) of the measurement, the position of the landmark in
% the coordinate frame of the robot given by the vector x
%
% Output
% e 2x1 error of the constraint
% A 2x3 Jaco... |
function [w2] = fitlinreg(y,X,lambda)
w2 = (X' * X + (lambda*eye(size(X,2)))) \ (X' * y); |
function [obj,ctrl_prob,gp_prob] = solve_HIFOO(obj,ctrl_prob,gp_prob)
% Set options for controller design <- needs nice way to set them
options.cpumax = 10;
options.nrand = 5;
options.epsilon = 0;
% options.fast = 1;
% set up some handy variables
nobj = ctrl_prob.nobj;
ncon = lengt... |
function loglikelihood = ComputeLogLikelihood(P, G, dataset)
% returns the (natural) log-likelihood of data given the model and graph structure
%
% Inputs:
% P: struct array parameters (explained in PA description)
% G: graph structure and parameterization (explained in PA description)
%
% NOTICE that G could be eit... |
clear variables;
close all;
n_cases=24;
cx=[0:n_cases];
cy=[0:n_cases];
[CX,CY]=meshgrid(cx,cy);
hold on;
mesh(CX,CY,zeros(n_cases+1,n_cases+1));
M = zeros(n_cases,n_cases);
for k = 1:537
a = 1;
switch a
case 0
x = (n_cases) * rand();
y = (n_cases) * rand();
plot... |
clear all;
images = dir('./imgre/ojo*.jpg');
for img = 3:length(images)
redEye = imread(['./imgre/',images(img).name]);
figure, subplot(2,1,1), imshow(redEye);
mask = getMask2(redEye);
subplot(2,1,2), imshow(mask);
end
|
% show slices and points given the brain area
%**************************************************************************
function[] = showSlicesOfArea(string)
% string is a string including acronym of brain areas, / as separator
% location of object points
pointListFolder = 'H:\NP histology\probe_points';
% ... |
classdef sphericalHarmonicsMatrix < matlab.mixin.SetGet
%SPHERICALHARMONICSMATRIX: this class holds the coefficients and data for conversion to and from SH domain.
% Constructor:
% sh = sphericalHarmonicsMatrix;
% creates an empty object. We need to populate this with the order, compute the T matr... |
function A = generateSPDmatrix(n)
% Generate a dense n x n symmetric, positive definite matrix
A = rand(n,n); % generate a random n x n matrix
% construct a symmetric matrix using either
A = 0.5*(A+A'); %OR
%A = A*A';
% The first is significantly faster: O(n^2) compared to O(n^3)
% since A(i,j) < 1 by construction a... |
function save_figure( figure, name, height, width )
FIGURES_DIR = 'figures';
% Format figure to specified size
set(figure,'Units','inches');
set(figure,'Position', [1 1 width height]);
set(figure,'PaperPositionMode','auto');
%set(figure,'Units','normalized','Position',[0.15 0.2 0.75 0.7]);
% Find the current... |
function [ cache, cache_index ] = cache_get_entry_by_hash( cache, yhash_i, psi_i, loss_i, ...
cache_scores, max_cache_size, removeFromActiveSetIfFullCache )
% [ cache, cache_index ] = cache_get_entry_by_hash( cache, yhash_i, psi_i, loss_i, ...
% cache_scores, max_cache_size, removeFromActiveSetIfFullCache )
%
%... |
function mysim_nav_swarm_comms
% initial dynamic state [pos;vel] in 2D
% each column is one agent
% random initial position, stopped
Nagents = 30;
x = [3*2*(rand(2,Nagents)-0.5)-3;
zeros(2,Nagents)];
% initial channel simulation for comms
channel = initChannel();
% initial decision maker memory
% same for each a... |
% Clear the command window
clc;
%% Estimation with linear hedonic price gradient
% Perparing First Round Variables/Data
n = numel(Y);
p = Y';
intercept = ones(2404,1);
x = [intercept walleye salmon panfish ramp restroom];
X_names = strvcat('intercept', 'walleye', 'salmon', 'panfish', 'ramp', 'restroom' );
for i = n... |
%Tally辅助变量最小二乘的递推算法
%Z(k+2)=1.5*Z(k+1)-0.7*Z(k)+u(k+1)+0.5*u(k)+e(k)，e(k)为有色噪声
%e(k)=v(k)+0.5*v(k-1)+0.2*v(k-2),v(k)为零均值的不相关随机噪声
%========================================
clear
clc
%==========产生M序列作为输入===============
x=[0 1 0 1 1 0 1 1 1]; %initial value
n=403; %n为脉冲数目
M=[]; %存放M 序列
for i=1:n
temp=xor(... |
% odev 3,
% katsayilar = polyfit(x,y,derece) ilgili katsayilar verir
% odevde polyfit kulanilmayacaktir!!!
%
% ornek
% Close all figures, clear variables in memory and MATLAB command screen
close all; clear all; clc;
% Set the output format to the short format with compact line spacing
format short; format compact;... |
clc;
close all;
%parzen window
%[fileID, errmsg] = fopen(filename);
%disp(errmsg)
nc = 3; % number of classes
[traindata] = textread('wine_uci_test.txt');
[testdata] = textread('wine_uci_train.txt');
testdata_size = size(testdata,1);
c = size(traindata,1)/nc;%number samples in each class
nf = size(traindata,2);% number... |
function [ polygon ] = Make( pixelList_xy, polyIdx, label, frame, color, reductions, quiet )
%[ polygon ] = D3d.Polygon.Make( pixelList_xy, polyIdx, label, frame, color, reductions, quiet )
if (~exist('color','var') || isempty(color))
color = [1,1,1,1];
end
if (~exist('label','var') || isempty(label))
label = ... |
function ret = open
ret = 1;
end |
function [plotCSV] = csvPlot( fileName )
fileName = csvread(fileName);
[m,n] = size(fileName);
joint1AngVel = fileName(:,1)'
joint2AngVel = fileName(:,2)';
joint3AngVel = fileName(:,3)';
time = fileName(:,4)';
figure(2)
hold on;
plot(time, joint1AngVel, time, joint2AngVel, time... |
function [net, stats] = loadState_deploy(fileName)
% -------------------------------------------------------------------------
load(fileName, 'net', 'stats') ;
net = dagnn.DagNN.loadobj(net) ; |
%function C_list = Search_Salient_points(Ds_i)
%clear all
Records =load('Senders and recievers.csv');
[~,j]=size(Records);
selected_user_number =400;
for user=1:selected_user_number %% Determine the number of users up to 400
Try(1,:) = Records(user,:); %% use to select user
Try(2,:)= [1 2 3 4 5 6 7 8 9 10];
C... |
%------------------------------------------------------------------------------------
% rh_temp_vertWindow.m
%
% analysis of multi-model data from RCEMIP, 21 models at time of writing
%
% creates plots of relative humidity, fractional detrainment rate, and wv lapse rate
% plotted as a function of temperature
%
% the wa... |
function [figureHandles, axesHandles] = PlotEdgesTimeAverage(roiSummaryMatrix,allParamsPlot,timeShift, duration, regCheck, numPhases, varargin)
detectorArray = true;
paramsPlot = allParamsPlot(1);
repeatSection = true;
barToCenter=2;
if any(strcmp(varargin, 'detectorArray'))
detectorArray = varargin{[false strcm... |
function SFNet = SFNG(Nodes, mlinks, seed)
seed = full(seed); %zabezpieczenie, zapisuje w postaci macierzy
pos = length(seed); %ilosc wezlow w macierzy seed
Net = zeros(Nodes, Nodes, 'single'); %tworzy macierz zerowa
Net(1:pos,1:pos) = seed; %przypisuje seed do glownej macierzy, by zaczac od tego miejsca
sumlinks = sum... |
%% build final models that only omits the last lasso iteration
% needed for face - noFace - whole brain contrast
clear;
%% Preparation
% CONSTANTS
NUM_OMIT = 1;
NUM_FOLDS = 10;
LABEL = 'TrueFaces';
% Load the results
wholeBrain = load('JLP_HF_TrueFaces.mat');
faceOnly = load('JLP_HF_onlyFace_TrueFaces.mat');
noFace... |
% Calculate responses for gaussian RBF units from sample vector x
function Phi = calcPhi(x, m, var);
%Dimension the function matrix fi
Phi = zeros(rows(x), rows(m));
%Calculate the RBF responses
for i = 1 : rows(x)
Phi(i, :) = gauss(x(i, :), m, var)';
end
|
function [m, var] = initrbf(units, dims, dmin, dmax);
% plots rbf set two dimensionally as points. p1 and p2 are the actual
% dimensions plotted. Here we assume that the variances per unit are
% one dimensional.
%i=rows(m);
span = abs(dmax - dmin);
m = rand(units, dims)*span + min(dmin, dmax);
sdev = 0.1*span*ones(unit... |
function [ GMST ] = MJD2GMST( MJD )
%[ GMST ] = MJD2GMST( MJD ) Convert Modifided Julian Date to Greenwhich
%Mean Siderial Time
% INPUT
% MJD - Modified Julian Date
% OUTPUT
% GMST - Greenwhich Mean Sidereal Time
%
% Function by:
% Shawn Swist ~2018
GMST = 280.4606 + 360.9856473*(MJD-51544.5);
... |
function theta = PPLR(X,y,epsilon,initial_theta)
[~,N] = size(X);
lambda1 = 2;
t = gamrnd(N,2/(epsilon*N*lambda1) );
b = rand( N,1 );
s = sign(rand(N,1)-0.5);
b = s.*b/norm(b)*t;
[theta, cost] = fminunc(@(t)(objFunction_PPLR(t, X...
, y ,b )), initial_theta);
end |
% comment
classdef runSim
properties
basePath = '/Users/jeremysment/Documents/ClassWork/ClassesF12/NeuralNetworks/ProjectDocs2012/Project/svn/'
%basePath = '/Users/casper/cs547-svn/';
end
methods
% Called first to load the jar
function init(this)
javaaddpa... |
function [ref_x] = jeden_krok(r,okno)
%Funkce jeden_krok stanovuje vlnu/kmit, který je charakteristický
%u konkréního naměřeného signálu pro jeden krok.
%Vstupy:
% r = vstupní signál
% okno = délka okna, které klouže po signálu, pomocí kterého se
% signál po určitých charakteristický... |
function [output] = mapingF(block, subkey)
b1 = block(1);
b2 = block(2);
b3 = block(3);
b4 = block(4);
k11 = subkey(1);
k12 = subkey(2);
k13 = subkey(3);
k14 = subkey(4);
k21 = subkey(5);
k22 = subkey(6);
k23 = subkey(7);
k24 = subkey(8);
% expansion / permutation of input block
ep = horzcat(b4, b1, b2,... |
function [y] = ex_post_W1(a,b,c1,x,c2,n,k,th1)
% What is the equilibrium demand and price?
Qs = exp(a-b*(c1+x));
Q2 = max(0,c1+x+th1-c2);
if Q2 <= Qs;
p = c1+x;
else;
q0 = [Qs exp(a)];
Q2 = fzero(@m1_comp_Q,q0,[],a,b,c2,th1);
p = (a-log(Q2))/b;
end
CS = exp(a-b*p)/b;
PS = Q2^2/2;
... |
function lr_test(name)
disp('======Training======');
% load data from csv files
% data = importdata('data1_train.csv');
data = importdata(strcat('data/data',name,'_train.csv'));
X = data(:,1:2);
Y = data(:,3);
% Carry out training.
% outputs an approximation of a function's gradient
% fn: function whose gradient is... |
%% 时域信号
Fs=1000; %采用频率
f1=50;f2=125;f3=135;
N=5012;Nfft=N;n=0:N-1;t=n/Fs; %采用的时间序列
xn=cos(2*pi*f1*t)+1.5*cos(2*pi*f2*t)+cos(2*pi*f3*t)+1.5*randn(size(n));
figure;
plot(t,xn);grid on;title('时域信号 t——y ');
%%
% 该函数计算的是功率谱归一化后的结果，计算公式中还除了Fs，量纲为dB/Hz。
% 比普通的周期图法大大约3dB
window= boxcar(length(xn)); ... |
function [u_T, lambda_T] = Autov(A)
%%
%Compute the eigenvector assiacted with the largest eigenvalue and the eigvenctor
% of a adjacency matrix A.
% Input:
% A: Adjacency Matrix
% Output
% u_T: Eigenvector
% lambda_T: Largest eigenvalue
%%
[W, D] = eig(A);% V eigenvector column % D diagonal matrix ... |
function [ a ] = Zhang_CoSaMP( u,Phi,s )
% CoSaOMP construct a signal approximation given the compressive samples.
% Based on the CoSaMP algorithm proposed in "Iterative signal recovery from incomplete and inaccurate samples"
% Detailed explanation goes here
% input u(R*1) is the noisy sample vector
% inp... |
function [W,C,Lambda,avgAc,stdAc,accuracy] = calculation(X,Y)
[numFeature,numSample]=size(X);
class1=X(:,1:numSample/2);
class2=X(:,numSample/2+1:numSample);
label1=Y(1:numSample/2);
label2=Y(numSample/2+1:numSample);
setPara.W=ones(numFeature,1);
setPara.C=0;
setPara.t=1;
setPara.Epsilon=0.000001;
setPara.Beta=15;
se... |
function Exp= initTriggers(Exp)
%======================
%SET TRIGGER PROPERTIES
%======================
% Create a device object
% dio = digitalio('nidaq',1);
% warning('off', 'daq:digitalio:adaptorobsolete');
% dio = digitalio('parallel','LPT1');
daqhwinfo('parallel');
Exp.Trigger.dio = digitalio('parallel'... |
function idof = smoothitudc_idof (time, dof, itime, inum, dt, idof_method, ignore_self)
%SMOOTHITUDC_IDOF Interpolation of degree-of-freedom for smooothitudc.
if (idof_method==0), idof = []; return; end
if isscalar(dof)
idof_sum = inum * dof;
else
[idof_sum, idof_avg] = smoothit (time, dof, dt, itime... |
load('f10.mat');
cols = [0.9 0.3 0.3; 0.3 0.3 0.3];
f=figure;
mhi = squeeze(mean(d));
ehi = squeeze(std(d)./sqrt(size(d,1)));
e=errorbar([1 1; 2 2], mhi, ehi, 'LineWidth', 1.2);
e(1).Color =cols(1,:);
e(2).Color = cols(2,:);
ylim([0 0.6]);
xlim([0.5 2.5]);
t=gca;
t.XTick=[1 2];
halfstr ={'First Half', 'Second Half'}... |
function startRpts(appName)
% startRpts(appName)
% Sets the 'rptMsgFlag' field of all applications under the APPS
% structure to true if no arguments are given. Otherwise, turns on
% the rptMsgFlag of the application whose field name under APPS is
% specified by the string 'appName'.
%
% Usage: startRpts
% sta... |
% ti_checkerboard_2d: 2D checkerboard TI
%
% TI=ti_checkerboard_2d(w,N,ncat)
% w: width of checkerboard
% N: Number if pixels in each direction
% ncat: Number of categories
%
%
% examples:
% TI = ti_checkerboard_2d(2);
% TI = ti_checkerboard_2d(3,10);
% TI = ti_checkerboard_2d([3 3],[30... |
function [avg, bins] = isoscalar_average(data, scalar, bins)
if isscalar(bins)
bins = linspace(min(scalar), max(scalar), bins);
elseif isvector(bins)
bins = bins;
end
Y = discretize(scalar, bins); % this is the slow step
avg = nan(size(data, 1), length(bins)-1);
for binindex=1... |
classdef location < handle
properties
ID;
database_index;
index;
x;
y;
group;
end
properties(Constant,Hidden)
INDEXcol =2;
Xcol = 3;
Ycol = 4;
GROUPcol = 5;
IDcol = 6;
end
... |
function PhasePanel=PhaseHARHAR(T, EXP);
% PhaseHARHAR - Phase panel for the HARHAR stimulus GUIs.
% F=PhaseHARHAR(Title, EXP) returns a GUIpanel F allowing the
% user to specify the phase component of the harmonic.
% The Guipanel F has title Title. EXP is the experiment
% definition, from which the number of... |
function result=perimeter_in(long,lat,fire_area,wrfout,time_now,time,interval,count);
% Volodymyr Kondratenko July 19 2013
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Input:
% long,lat longtitude and latitude converted to meters
% fire_area fire map,[0,... |
function [tsnp, err, errmsg] = tsnpimporti(fts, varargin)
% (c) Jianhua Zhou 2012, 2013, 2014
%
% Description: imports network parameters in Touchstone file,
% returns the S,Z,Y and other allowable network parameter data in tsnp struct.
% noise data is ignored
% Input variables:
% ... |
%==数据预处理=====
close all;
for i = 1979:2016
year_num = int2str(i);
dataname = ['./data/',year_num,'_area.txt'];
[y,m,d,Data,Minimum,b10,b30,Mean,b70,b90,Maximum] = textread(dataname, ...
'%d-%d-%d %f %f %f %f %f %f %f %f',360,'headerlines',6);
nan_colm = find(Data == -9999);
Data(nan_col... |
%
% Copyright 2016 Vienna University of Technology.
% Institute of Computer Graphics and Algorithms.
%
function[P1P2_saved, P2P3_saved, P3P1_saved, Normal_normalized, P1P2_length, P2P3_length, P3P1_length, Area, alpha, beta, gamma, angles_sum, angles_max, angles_min, angles_avg] = Triangles()
%% General Hints:
% If yo... |
function result = NatureNeighborSpectralClustering(filename)
X = load([strtrim(filename),'.txt']);
C_Label = load([strtrim(filename),'_label.txt']);
K = length(unique(C_Label)); % Number of clusters
N = size(X,1);
Dist = squareform(pdist(X));
sigma = max(Dist(:));
tmp = Dist.^2/sigma;
A = exp(-tmp);
Na... |
function latex_string = tableLatex(input_table, with_table_environment, with_resize, table_name)
export_as_file = false;
with_resize = false;
if (nargin < 2)
with_table_environment = false;
table_name = '';
elseif (nargin < 3)
table_name = '';
elseif (nargin < 4)
ta... |
% Roselynn Conrady M E 556
% MATLAB image from Lecture 3 and 4
clear all; close all;
I = imread('photo_sample.jpg');
I1 = rgb2gray(I);
I2 = imnoise(I1, 'gaussian'); % adding noise
figure, imshow(uint8(I2))
% Median filtering w/o built in function
FS = 3; sigma = FS/3;
[rows, cols] = size(I1);
I2 = I1;
for i = (F... |
function emotion = emotion_detector(neutral, extreme)
%import image data as taken from clm_trackr
data = dataInit();
[~, ~, ~, Mdl] = svm_classify(data);
[~, e_align] = procrustes(neutral,extreme);
emotion_feature = neutral - e_align;
confidences = zeros([1,length(Mdl)]);
for i = 1:length(Mdl)
[~, score] = predi... |
clc;
close all;
clear all;
x=imread('cameraman.tif');
subplot(3,3,1);
imshow(x);
title('colour image');
for i=1:256
for j=1:256
y(j,i)=x(257-i,j);
end
end
subplot(3,3,2);
imshow(y);
title('rotate 90 degree');
for i=1:256
for j=1:256
z(j,i)=y(257-i,j);
end
end
... |
%
% hw1q2_ADALINE.m--
%
%
% Developed in Matlab 9.5.0.944444 (R2018b) on Debian 9.
% Ayberk Karaakın (ayberk.ka@gmail.com), 29.10.2018
% Repository: https://github.com/akarakn/Perceptron-ADALINE.git
%-------------------------------------------------------------------------
%----------------------------Not workin... |
% FAST-ADAMS-Simulink CertTest comparisons:
function PlotCertTestResults( newPath, oldPath, PlotFAST, PlotAdams, PlotSimulink )
%function PlotCertTestResults( newPath, oldPath, PlotFAST, PlotAdams, PlotSimulink )
% This function plots the FAST, ADAMS, and/or FAST_SFunc CertTest results,
% comparing .out/.plt, .elm, .... |
function length = GetPathLength(path,cityLocation)
% Reusing already written function
length = CalculateRouteLength(path, cityLocation);
end
|
function valid = ishandleandvalid(h)
valid = ~isempty(h) && isvalid(h);
end |
Vin = 0.002;
L = 1.5;
W = 0.8;
h0 = 0.5;
D = 0.038;
g = 9.81;
uout = @(h) sqrt(g*h/2.5);
func = @(t,h) Vin/L/W - pi*D^2/4/L/W*uout(h);
[t,h] = ode45(func,[0,900],h0);
plot(t,h,'*');
xlabel('time (s)'); ylabel('height (m)');
grid on; |
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