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function [R, sunpos] = svLocalFrame(svPos,epochs,sunpos)
% function to create the satellite local frame rotation matrix
% offsetECEF = R(:,:,i)*offset;
if nargin < 3
% if isempty(strfind(path,'\mice\src\mic'))
% AttachToMice();
% end
% get sun position for each time
jd = epochs2jd(epochs);... |
function savejs()
load('torch/trainData.mat');
data = double(train_data);
save('trainData.txt', 'data');
load('torch/testData.mat');
data = double(test_data);
save('testData.txt', 'data');
load('torch/trainLabel.mat');
train_label = double(train_label');
save('trainLabel.txt', 'train_label');
load('torch/testLabel.... |
function [Xn T] = normalizePoints(Xh)
m = mean(Xh(1:2, :), 2);
d = mean(sqrt((Xh(1, :) - m(1)).^2 + (Xh(2, :) - m(2)).^2));
s = sqrt(2) / sqrt(d);
T = [s 0 -s * m(1);
0 s -s * m(2);
0 0 1];
Xn = T * Xh;
end
|
function NewMask=watershedSegment(ImageFrame,Mask,seedMask)
oldMask=Mask;
I_eq_c = imcomplement(ImageFrame); %complement the image because we are about to apply the watershed transform, which identifies low points, not high points.
mask_em=seedMask;
mask_em(mask_em>1)=1;
mask_em(1,:)=0;
mask_em(:,1)=0;
mask_em... |
function out = tswopOneRandomNoise(x)
out = zeros(size(x));
out(:,:) = x(:,:);
i = randi(size(x,2));
out(:,i) = rand(2,1) .* 2 -1; |
%BPneuron 算法实现
%@Author：alicewithrabbit
%email：imroxaswc@gmail.com
%release date：2016/9/6
%未采用最新的feedforwardnet函数，感觉不太好用
%读取训练数据
clc;clear;
fid=fopen('Iris_train_data.txt');
train_data=textscan(fid, '%f%f%f%f%f',75);
f1=cell2mat(train_data(1));
f2=cell2mat(train_data(2));
f3=cell2mat(train_data(3));
f4=cell2mat(train_d... |
function M = tensor_mul(T, v, d, mode)
%TENSOR_MUL is the tensor multiply function
% T is a tensor
% v is a vector
% d is the dimension
shape = size(T);
if mode == 0
shape_T = int32(ones([1, d]));
shape_T(1:length(shape)) = shape;
T = reshape(T, shape_T);
shape_v ... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ETH Zurich, Switzerland
% Separation Processes Laboratory
%
% Project: Lithoplatelets
% Year: 2021
% MATLAB: R2019b, Windows 64bit
% Authors: Anna Jaeggi (AJ)
%
% Purpose:
% Post-process and plot the orientati... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 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#... |
function [ validPublish ] = PublishResults(pulseData,handles)
%publish results into table
validPublish = 0;
try
voltage = pulseData.nSig.Vptp/1000;
P4P2 = round((pulseData.pulseResult(1,1)*100))/100;
P3P1 = round((pulseData.pulseResult(1,2)*100))/100;
N4N2 = round((pulseData.pulseResult(1,3)*100))/100;... |
% lookupGeometries.m:
% Takes in a 12-column momentum lookup table `table`, an auxillary lookup
% table `auxtable` for storing results from extra simulations, a list of
% momentum triples `momenta` that you want to find geometries for and an
% error tolerance to aim for.
%
% It will return a matrix bestGeometries with... |
clear
load pretest.mat
fs = 30;
shift = 0.2;
t = ((1:24)/fs)'+shift;
for sub = 1:size(width_pretest, 3)
pretest_sub = squeeze(width_pretest(:,:,sub));
xx = pretest_sub(:,4) == 0;pretest_sub(xx,4) = 2;
idx1 = ~isnan(pretest_sub(:,4)) & (pretest_sub(:,4) == pretest_sub(:,2));
idx2 = ~isnan(pretest_s... |
function [delXG, delYG] = GoalDelta(vx, vy, gx, gy, goalR, goalS, alpha)
% This function gives delX, delY of attraction caused by the goal point
dGoal = sqrt((gx-vx)^2 + (gy-vy)^2); % distance bw goal and current position
thetaG = atan2((gy-vy),(gx-vx)); % angle between goal and current position
% delXG = 0; delYG... |
addpath RWTHMindstormsNXT;
%establish memory map to status.txt.
fstatus = memmapfile('status.txt', 'Writable', true, 'Format', 'int8');
fstatus.Data(6) = 49;
j3 = memmapfile('junction3.txt', 'Writable', true);
%open config file and save variable names and values column 1 and 2
%respectively.
config = fopen('c... |
function out = merge(input1, input2)
%function out = merge(input1, input2)
% combines two matrices size by side and pads the one with smaller length
% with NaNs at the bottom
%P Robbins 2/95
out=[]; l1 = []; l2 = []; w1 = []; w2 = [];
[l1,w1] = size(input1);
[l2,w2] = size(input2);
if l1 == l2
o... |
classdef LMNNet < handle
% This class performs training of a LMNNN multi-layer neural-net.
%
properties
% act_func is an ActFunc instance for computing feed-forward activation
% levels in hidden layers and backpropagating gradients
act_func
% out_func is an ActFunc insta... |
function writeSmoothAbs()
%
% FUNCTION:
% This function is used to write the code for smoothAbs
%
MaxOrder = 8; %Should be at least 1
N = MaxOrder + 1;
%% Set up the constraints:
% The value and slope should be 1 at the right transition point, and zero
% for any higher derivatives.
xRight = ones(1,N)... |
%--------------------------------------------------------------------------
queue(id_min,:)=[]; %删除要发生的事件
count=count-1;
%--------------------------------------------------------------------------
if mark_j>0 %颗粒之间碰撞
id=queue(1:count,2:3)==mark... |
clear all ; close all
subs = {'alex','dina','genevieve','jeremie','russell','valerie'} ;
comps = {1:64,1:64,1:64,1:64,1:64,1:64} ; % all subjects, right and left
fcomps = {[64,80,12],[41,31,40],[61,48,15],[6,84,79],[79,80,50],[75,77,41]} ;
latvis_fmri = [25,23,40,21,50,20] ;
latvis_eeg = [26,14;16,6;11,23;... |
load (fullfile('Train','Train.mat'));
%%
offsets=[0 1; -1 1;-1 0;-1 -1];
for i = 1:size(imgResize,1)
grayImage = rgb2gray(imgResize{i});
% glcm =graycomatrix(grayImage,'Offset',[0 pixel_dist; -pixel_dist pixel_dist; -pixel_dist 0; -pixel_dist -pixel_dist]);
% [glcmfeature,GlcmImage] = graycoprops(glcm,{'All... |
%Here are test code
rgb_img = 'stego_white_pocket_test.bmp';
gray_img = 'lena_gray.bmp';
Bit_index = 8;
Bit_plane_analysis(rgb_img, Bit_index);
%Bit_plane_analysis(gray_img, Bit_index);
%============================= Display bit planes for image
%=======================
% @test_image: The test bitmap image file pa... |
function [points] = getHarrisPoints(I, alpha, k)
% Finds the corner points in an image using the Harris Corner detection algorithm
% Input:
% I: grayscale image
% alpha: number of points
% k: Harris parameter
% Output:
% points: point... |
function NS = make_NS()
NS.ode.fn = @NS_ode;
NS.fn = @NS_fun;
NS.dfdx = @NS_dfdx;
NS.dfdp = @NS_dfdp;
NS.d2fdx2 = @NS_d2fdx2;
NS.d2fdxdp = @NS_d2fdxdp;
end
|
% Problem 3 (d)
a0 = 0;
a1 = 2;
a2 = 1;
T = exp(linspace(0, 2i*pi, 500));
aT = a0*T.^0 + a1*T.^1 + a2*T.^2;
figure(5)
plot(real(aT), imag(aT), '-', "color", "black");
%plot(a^2 + b^2 = 1)
% Problem 3(e)
% 25 x 25 Toeplitz matrix
c25 = zeros(25,1) ;
r25 = zeros(1, 25) ;
c25(1, 1) = a0;
r25(1, 1) = a0;
r25(1, 2)... |
function [] = F3()
%Neville
input_file1 = fopen("realmadrid.txt", "r");
m = fscanf(input_file1, "%d", 1);
n = fscanf(input_file1, "%d", 1);
m
for i = 1:n + 1
tline = fgets(input_file1);
A = str2num(tline);
if(i == 1)
continue;
end
[t k] = size(A);
k = k / 2;
X = linspace(A(1), A(k), m);
... |
function y=shif(ns,nq);
%сдвиг элементов массива после уменьшения его длины nq
%на единицу
if nq~=0,
for i=1:nq,
ns(i)=ns(i+1);
end;
end;
y=ns; |
function lilycommand = find_lily_command()
% FIND_LILY_COMMAND - Returns the complete path of the lipyond executable.
% Lilypond must be previously installed. The searched path is:
% /Applications/LilyPond[*].app/Contents/Resources/bin/lilypond
%
% Usage: lilycommand = find_lily_command()
%
% Locate LilyPond's folder... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Sparse Representation recovery with L1Magic for face recognition
% z. li
% 2009.03.10
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear;
path(path, 'l1magic/Data');
path(path, 'l1magic/Optimization');
facep... |
clear; close all; clc;
%% constraint_viol &
CON_VIOL = nan(2426,15,4);
MAX_ITR = zeros(4,1);
REG_VIOL = cell(4,1);
%% load models
load('learned_functions/PVTOL_raw_100_new.mat');
max_itr = itr;
MAX_ITR(1) = max_itr;
CON_VIOL(:,1:max_itr,1) = constraint_viol(:,1:max_itr);
reg_err_all = zeros(itr,1);
viol_all = zer... |
function [results]=ABM_eval_uniform_incentive(rain_field_true,radar_field,gauge_xy,...
budget,alpha_P,max_par,min_par,rate,params,...
X,Y,folder,loop_ID)
% function to run the ABM model (based on uniform incentive)
% this function can also be used to test the performance of the optimized funct... |
function [y] = gabor_f(x)%%输出x的gabor变换，为长l=128的列向量
y = [];
t = 1:length(x);
for d = 0:log2(length(x))-2
a = 2^(2*d+2);
for p = 0:length(x)/(2^d)-1
b = p*2^d;
for q = 0:2^d-1
e = 2*pi*q/(2^d);
g = exp(-a*(t-b).^2+1i*e*t);
y = [y;sum(g'.*x)];
end
end... |
function u = controller(params, t, phi, phidot)
% STUDENT FILLS THIS OUT
%
% Initialize any added state like this:
%t
persistent newstate t_last
if isempty(newstate)
% initialize
newstate = 0;
t_last = 0;
end
dt = t_last - t;
newstate = newstate + dt*phi;
t_last = t;
k... |
Q_mean = 0;
for i = 1:(num_frames-2)
Q = q_fsB(frames(:,:,i),decod_frames(:,:,i));
Q_mean = Q_mean + Q;
end
Q_mean = Q_mean/(num_frames-2);
MSE_mean = 0;
for k = 1:(num_frames-2)
x=frames(:,:,k);
y=decod_frames(:,:,k);
MSE_1 = MSE(x,y);
MSE_mean = MSE_mean + MSE1;
end
MSE_mean = MSE_mea... |
function IFMCleanData = cleanIFM(bench, IFMData)
config = bench.config;
Percentil = config.ifmCleanPercentil;
% :TODO: check if it is the full pupill or the naomi pupill
Nexclude = int32(bench.meter2pixel(config.fullPupillDiameter) / 4.);
if nargin<2
if isempty(bench.IFMData)
error('IFM has not been measured... |
%--------------------------------------------------------------------------
%***********calculating the lower bound for parameter error****************
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
%Inputs:
... |
% dunn's index demo
clear all
clc
le=40;
data=random('Normal',0,1,le,2);
data=[data; random('Normal',2,1,le,2)];
idsR(1:le,1)=1;
idsR(le+1:2*le)=2;
distM=squareform(pdist(data));
[ids]=kmeans(data,2);
[ids2]=spectralClust(1,data,2,1);
disp(sprintf('Dunns index for kmeans %d', dunns(2,distM,ids)));
d... |
xxxxa=whos;
%xxxxnames=a.name;
%xxxxclasses=a.class;
for xxxxk=1:length(xxxxa)
if strcmp(xxxxa(xxxxk).class,'double')
assignin('base','xxxtest',b(:,idx2(k)));
xxxxa(xxxxk).name
s=eval('unique(xxxxa(xxxxk).name)')
pause
if length(s)==2
if... |
function [t,w,pedges] = GLinterval(a,b,NPanels,pedges)
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% [t,w,pedges] = GLinterval(a,b,NPanels)
% Returns nodes, weights and panel edges for composite 16 point
% Gauss-Legendre quadrature using NPanels equisized panels over (a,b)
%
% [... |
function uav_rs2hsc_posecalibration_rev2()
load rs0params.mat rs0params rs0_RTcol2dpt
load rs1params.mat rs1params rs1_RTcol2dpt
load setup.mat video_dir_uavcalib_uavrs video_dir_uavcalib_ugvrs ...
csv_dir_uavcalib_marker img_step squareSize time_margin
%UAVRSの動画
%動画からFrameを保存する
... |
function [epoch_std, year] = mydatestd (epoch)
temp = mydatevec(epoch);
year = temp(:,1);
[year_len, year_start] = mydatestd_aux(year);
std_year_len = mydatestd_aux();
epoch_std = (epoch - year_start) ./ year_len .* std_year_len;
end
%!test
%! % mydatestd()
%! test('mydatestd_aux')
... |
function [] = test_calc_b_LTX_2()
% function [] = test_calc_b_LTX_2()
%
% Make a grid
x_min = 0;
x_max = 0.8;
y_min = 0;
y_max = 0;
z_min = -0.5;
z_max = 0.5;
num_x_pts = 20;
num_y_pts = 1;
num_z_pts = 20;
num_contours = 20;
% % Make a grid
% x_min = -1;
% x_max = 1;
% y_min = -1;
% y_max = 1;
% z_min = -1.2;
% z_m... |
% Blair, Gupta, and Zhang 2008's ring attractor oscillatory interference model
% eric zilli - 20110908 - v1.0
%
% This manuscript deals with both grid and place cells, but this
% implementation focuses only on the grid cell component.
%
% (Notice this is the 1D version of the model, so the output is just a
% series o... |
%% Task 1: Linear Regression
% The task is based on the Machine Learning online course by Andrew Ng
% https://www.coursera.org/learn/machine-learning
% The dataset is taken from the MATLAB built-in datasets
%
% Instructions
% You will need to complete the following functions:
%
% plotData.m
% computeCost.m... |
function [X, d, XDefl, XBlock, dDefl, dBlock] = curtis_unitary_eig(Q)
[m, n] = size(Q);
% If w is an eigenvector of the Hermitian part of Q and the projection of
% Qw into the orthogonal complement of w has norm less than the following
% value, then w is deemed an eigenvector of Q.
% NOTE: It's not yet clear how to b... |
function [r q] = Find_RiskFree_and_Dividends_Shimko(C,P,K,S0,T)
% Estimates of the risk free rate and dividend yield from David Shimko.
% Requires inputs:
% C = Call prices
% P = Put prices
% K = Strikes
% S0 = Spot Price
% T = Time to maturity
% Returns:
% r = Estimate of the risk free rate
% q = Estimate ... |
% Exercise session 4: DMT-OFDM transmission scheme
clear all;
close all;
Nq = 6;
M = 2^Nq;
cpr = 600;
SNR = 25;
fftSize = 2^10;
frameSize = fftSize/2-1;
z=Nq*frameSize;
% Convert BMP image to bitstream
[bitStream, imageData, colorMap, imageSize, bitsPerPixel] = imagetobitstream('image.bmp');
% Append with zeros to ... |
function data = normalize(d)
% normalize(data) - scale before svm. Three different variants each giving different results
% the data is normalized so that max is 1, and min is 0 (-1)
% data = (d -repmat(min(d,[],1),size(d,1),1))*spdiags(1./(max(d,[],1)-min(d,[],1))',0,size(d,2),size(d,2));
% normD = range(d) + ep... |
% nuevo_vector=fuerzas_en_ejes_anatomicos(vector,eje_medial_lateral, eje_rotacion_int_ext,lado)
% La funcion recive como parametros una Fuerza en coordenadas globales y
% dos ejes anatomicos (eje medial/lateral y rotacion int/ext). Calcula el
% tercer eje anatómico y descompone el vector de fuerza en esos tres ejes.
%... |
function [ v ] = probvelocidad(q, params)
%Se definen las coordenadas generalizadas
x1=q(1);
y1=q(2);
x2=q(3);
theta=q(4);
%Se defininen las coordenadas que no varían con el tiempo
xA=0;
yA=0;
%Se llaman a las funciones de las restricciones y el jacobiano pues
%son necesarias para el cálculo de la velocidad
J=jacob(q,... |
% specsquare.m plot the spectrum of a square wave
f=1000; % "frequency" of square wave
phi = pi/4;
time=10; % length of time
Ts=1/10000; % time interval between samples
t=Ts:Ts:time; % create a time vector
% x=sign(cos(2*pi*f*t)); % square wav... |
function showExp(hObject)
data = guidata(hObject);
fprintf('*******************************\n');
fprintf('Trial 123, correct 80.2 %%\n');
fprintf('stim \tst Ton Toff parameters\n');
for i = 1:8
fprintf('%s \t %d %4d %4d',...
char(data.exp.names(i,2)),...
... |
function [ newGenome1,newGenome2 ] = CrossOver( Genome1,Genome2,positions )
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
newGenome1=Genome1;
newGenome2=Genome2;
crossOver=exprnd(10);
if crossOver < max(positions)
end
end
|
function [ M ] = diffMaps( E, l, E2, l2 )
% Compute the difference between the resulting segmentation and another
% (not necessarily a segmentation)
M=zeros(size(E));
for i=1:size(E,1)
for j=1:size(E,2)
for k=1:size(E,3)
if (E(i,j,k) == l && E2(i,j,k) < l2) || (E(i,j,k) ~= l && E2(i,j,k) >= l2)... |
function lidar_update(obj, z, params)
obj.XX(params.ind_yaw)= pi_to_pi( obj.XX(params.ind_yaw) );
%if all(obj.association == 0)
% obj.n_k= 0;
% obj.Y_k= [];
% obj.L_k= [];
% obj.gamma_k= [];
% obj.q_k= 0;
% obj.H_k= [];
% obj.number_of_associated_LMs= 0;
% return;
%end
association = obj.ass... |
function [S_x,S_y]= smoothing_filter(x,y)
for i=3:length(y)-2
S_y(i)=(y(i-2)+y(i-1)+y(i)+y(i+1)+y(i+2))/5;
end
S_y = S_y(3:length(S_y));
%
S_x = x(3:length(x)-2);
end
|
function aabb=makeAabb(side,centroid)
% Make a cubic scene AABB with given side length, centred at centroid.
if nargin<2
centroid=[0 0 0];
end
aabb=0.5*side*[-1 -1 -1 1 1 1]+[centroid centroid]; |
function [eqtQ,eqt,sbs]=p_equal_treatmentQ(clv,x,tol)
% P_EQUAL_TREATMENTQ checks if the vector x satisfies the equal
% treatment property (ETP) using Matlab's PCT.
%
% Usage: [eqtQ,eqt]=clv.p_equal_treatmentQ(x,tol)
%
% Define variables:
% output:
% eqtQ -- Returns true (1) if the solution x satisfies ETP,
% ... |
% IRIN - Arquitectura Comportamiento
%
% Diego Dominguez
% Miguel Reino
% Andres Ripoll
%
%% Borrado de las variables de entorno
clear;
% Su código aquí
%% 1 - Recorrido comportamiento
filename = 'robotPositionComp';
delimiterIn = ' ';
headerlinesIn = 1;
A = importdata(filename,delimiterIn,headerline... |
function presentStimuli(wPtr, trialAngles, locations, cont, phase_offset)
global params;
% Inpute:
% Angles - is an array of angles to present each gabor
% locations - is a matrix of n*2 location of each corresponding stimulus
% This function will draw all the stimuli rotated by angles in the specific
% location... |
%=========================================================================
%
% Program to investigate the effects of heteroskedasticity
% on the size of the trace test of cointegration
%
%=========================================================================
function coint_hetero( )
clear all
clc
... |
% [avge,maxe] = Ipedmerror(PL,PU,D)
%
% compute the average and max edge error between a partial EDM D
% and the bound pEDMs PL,PU.
function [avge,maxe] = Ipedmerror(PL,PU,D)
[n,n] = size(PL);
avge = 0;
maxe = 0;
m = 0;
e = 0;
for i=1:n
for j=1:n
if (PL(i,j)>0)
e = max(PL(i,j)-D(i,j),0)... |
function Lf = drift_L(dt, xGauss, mu0)
if (abs(dt) > 1.e-14)
a = xGauss(1)/(1-xGauss(2)^2-xGauss(3)^2);
T = 2*pi*sqrt(a^3/mu0); % Orbit period
dt = mod(dt,T);
L0 = xGauss(6);
OptionsOde = odeset('AbsTol',1.e-12,'RelTol',1.e-12);
... |
% Amir kabir University of Technology (Tehran Polytechnic)
% Computer & Information Technology Engineering Department
% Resource Allocation in Wireless Networks
% DTPC Simulation using MATLAB
% Programmer: SeyedHedayat Hosseini
% Date: December, 2015
% Matlab Version: R2014b
% ************* MAIN SCRIPT *********... |
function fDyn = getDyn(A, B, X0, Px, Pu)
% returns dynamical constraints
global u x;
% number of agents
N = length(u);
% time horizon
h = size(u{1},2);
fDyn = [];
for n = 1:N
x{n} = X0(:,n);
for t = 1:h
% System dynamics
xt = x{n}(:,t);
ut = u{n}(:,t);
x{n} = [x{n}, A... |
%----------------------Experiment 1----------------------------------------
[t1,m,Fs] = signalGenerator(); %taking input from Signal Generator in time domain
legend('m(t)')
%--------------------------------------------------------------------------
frequency_domain = fft(m);
frequency_domain_1 = fftshift(frequenc... |
% Ejemplo Convolucion 1D en el dominio del espacio y frecuencia
%
% D.Mery, PUC-DCC, Septiembre 2017
% http://dmery.ing.puc.cl
close all
N1 = 1000;
N2 = 17;
f1 = 2*sin((1:N1)'/N1*2*pi*10)+rand(N1,1)-0.5;
f2 = ones(N2,1)/N2;
figure(1)
plot(f1)
title('sinus+noise')
g = conv(f1,f2);
f1p = [f1; zeros(N2-1,1)];
f2p = [f2... |
function ip=a_init_dev
ip(1).aliases={'T_K' 'T_C'};
ip(1).units={'K' 'C'};
ip(1).full_name='Operating Temperature';
ip(1).type='number';
ip(1).n=[1 1;1 1];
ip(1).range=[-inf inf];
ip(1).values={};
ip(1).default=[300];
ip(2).aliases={'type'};
ip(2).units='';
ip(2).full_name='Device Type';
ip(2).type='string';
ip(2).n=... |
%read data from simlation
[f,a,p] = textread('C:\Documents and Settings\Bruce Land\My Documents\WebSites\ece576\DDA\AnalogSimNiosII\SimData2.txt',...
'freq=%f, amp=%f, phase=%f')
[f,i] = sort(f);
a = a(i);
p = p(i);
figure(1), clf;
subplot(2,1,1)
semilogy(log10(f),a,'bo','markersize',4)
line([log10(4... |
function Sproj_analysisPipe_plotStats_topoER(stat,lay)
%% ft_topoplotER
stat.mymodel = stat.model{1}.weights;
load('C:\Users\Admin\Desktop\FieldTrip\fieldtrip-20180128\template\layout\easycapM20.mat');
cfg = [];
figure
cfg.parameter = 'mymodel';
cfg.layout = lay;
cfg.comment = '';
... |
% -----------------------------------------------------------
% -----------------------------------------------------------
% f------The Observed Picture(M*N);
% phi------Signed Distance for Segamentation(M*N);
% p------The introduced Auxillary Variable, p = (phi_x, phi_y), (M*N,M*N);
% n------The introduced Auxillary ... |
function [nelio,points] = tarkistajaeliminoi(indeksi,points,suunta)
%%%%% tarkistaa indeksiä vastaavan pisteen ympäristön ja eliminoi, mikäli mahdollista.
%%%%% palauttaa asetetun nelion ja uuden pistejoukon
nelio=[];
piste = points(indeksi,:);
%%%% poistetaan peruspiste joukosta
%%% indeksit = [1:indeksi-1,indeksi+1:... |
function varargout = getargs(args,default_values)
%GETARGS Process positional arguments from the input arguments
%
%ARGOUT=GETARGS(ARGIN,DEFAULT_VALUES) processes input arguments (typically
% from VARARGIN), by replacing DEFAULT_VALUES by valid ARGS items
% (items different from [], the empty numeric array)
%
%ARGOUT: ... |
% Plot one example of the mixture, groundtruth and separated results for
% 2-source conditions
clear all; close all; clc
sample_i = 126;
source_i = 1; % show the first signal
SourceNumber = 2;
data_dir = sprintf('/vol/vssp/ucdatasets/s3a/Qingju/EusipcoEvalResult/Mixture%d/',SourceNumber)
taglegArray = {{'Oracle IBM',... |
function output = get_gamma_dot_c_DSEA(t, y, tau_r, config)
% Get the control input for the current state and desired reference moment,
% using the DSEA method, which is presented in
% Valk, L., Berry, A., and Vallery, H.,
% "Directional Singularity Escape and Avoidance for Single-Gimbal Control Moment Gyroscopes,"
% ... |
classdef NLDemand < Estimate
% Estimation and simulation code for nested logit.
properties
alpha
sigma
d % Utility without the price effect
end
properties (SetAccess = protected, Hidden = true )
marketid % Protected?
nestCount = 0
nest
... |
Btot_PR_map=sqrt(Bpol_PR_map.^2+Btor_PR_map.^2);
finesse_data_X=reshape((Rpos_PR_map(:,:)-R0),NP*Nradial,1);
finesse_data_Z=reshape(Z_PR_map(:,:),NP*Nradial,1);
[XX,ZZ] = meshgrid(X_scale,Z_scale);
frame_rank=1001;
disp('loading new frame rank#');
disp(frame_rank);
f=frame_rank;
if (f<10)
frame_name='00';
else... |
% ------------------------------------------------------------------------
% script to plot ecotron variable anomalies in different periods
% initalise
close all
axcolor = [0.3 0.3 0.3];
cmap_temperature = flipud(mf_colormap_cpt('temperature'));
cmap_tas = flipud(cmap_temperature(1:6,:));
cmap_pr = flipud(mf_colorma... |
function [area] = energy_enclosed(fn,x,y)
%xx = meshgrid(x,x);
%yy = meshgrid(y,y);
%[xx yy] = meshgrid(x,y);
rho = sqrt(x.^2+y.^2);
tMin = 0; % angle
tMax = 2*pi;
rhoMin = min(min(rho));
rhoMax = max(max(rho));
%fn(rho > rhoMax/2) = 0;
%fn(rho > 5) = 0;
fn
rho
fn = rho .* fn
area... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CZ4003 - COMPUTER VISION %
% LAB 2 %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Edge Detection + Hough... |
function oe = eci2oe(state, GM)
r_ijk = state(1:3);
v_ijk = state(4:6);
r = norm(r_ijk);
v = norm(v_ijk);
% Create all necessary vectors
hVec = cross(r_ijk, v_ijk);
h = norm(hVec);
nVec = cross([0, 0, 1], hVec);
n = norm(nVec);
eVec = (1/GM)*((v^2 - GM/r)*r_ijk - dot(r_ijk, v_ijk)*v_ijk);
e = norm(eVec);
% Compute... |
function [expectation_Psoriasis, expectation_Seboreic, expectation_Lichen, expectation_ptyriasisRosea,expectation_cronisdermatitis,expectation_pityriasisRubraPilaris,variance_Psoriasis,variance_Seboreic,variance_Lichen,variance_ptyriasisRosea,variance_cronisdermatitis,variance_pityriasisRubraPilaris] = compute_expectat... |
%THIS code is used to calculate P and F for the given blade;
clear
clc
R=5;%radius of rotor
B=3;%number of blades;
V_0=10;
n=3000/60;%this is the rotational speed in rpm;
rho_a=1.225;%the density of the atmosphere;
beta_p=0;%pitch angle;
n_element=8;%the number of ring elements;
omega=n*2*pi;%angular velocity;
for i=... |
function varargout = shared(varargin)
%SHARED Get a shared (owning) reference.
%
% [{DM} OUTPUT1, {DM} OUTPUT2, {DM} OUTPUT3] = SHARED({DM} ex, char v_prefix, char v_suffix)
% [{SX} OUTPUT1, {SX} OUTPUT2, {SX} OUTPUT3] = SHARED({SX} ex, char v_prefix, char v_suffix)
% [{MX} OUTPUT1, {MX} OUTPUT2,... |
% This is material illustrating the methods from the book
% Financial Modelling - Theory, Implementation and Practice with Matlab
% source
% Wiley Finance Series
% ISBN 978-0-470-74489-5
%
% Date: 02.05.2012
%
% Authors: Joerg Kienitz
% Daniel Wetterau
%
% Please send comments, suggestions, bugs,... |
function BW_seedpoints=select_seedpoints(Global_BW,objects_num)
% This function is for selecting the large objects in the global detection results
% as the seed points for the watershed method
%
% Input: im_ori = an astronomical image
% Global_BW = a binary image which is objects detection results,the value 1
... |
function [H, f, A_constr, b_constr] = make_QP(T, uT, uK, A, B, theta, x0, Qf, qf, Q, q, R, r, Hx, hx, Hu, hu)
%%% augmented system form %%%
% system is assumed to be in augmented form %
% augmented state is [x(t) u(t)]^T %
% du(t) is input to augmented system %
% input to syst... |
% script to test guided filter
% calling filtered = guilded_filter(input, guide, epsilon, win_size)
original = imread('peppers256.png');
original = double(original);
original = original / 255;
sd = sqrt(.001);
win_size = 5;
input = imnoise(original, 'gaussian', 0, sd*sd);
guide = input;
filtered = guid... |
function [ x1, y ] = kesisim( x1, y1, x2, y2 )
y=[];
for k=1:length(x1)
y(k)=min(y1(k),y2(k));
end
end
|
function isInside = sys( x, y )
if( x^2 + y^2 < 15 ),
isInside = 1 ;
else
isInside = 0 ;
end
|
%% Homework 3
% Ezra Davis (epd9)
%% 1 Linear Independence and basis
%% 1a
% $\alpha \vec u + \beta \vec v = [6.5, 0.5]^T$ is a linear combination of
% $\vec u$ and $\vec b$ by definition because it is the sum of scalar
% multiplications of $\vec u$ and $\vec b$.
alpha = 2;
beta = 1.5;
u = [1, 1].';
v = [3, -1].';
alph... |
% This script takes as input a sequence of images (specified by dataFile)
% and converts them to an aedat-logfile composed of events.
% It also converts the ground truth of the flow field between two frames
% (given in a flo-file specified by gtFrame) to event-based ground truth (a
% mat-file gtEvent with three 2... |
function varargout = plot(obj,alpha)
plot(obj.Support,0.25)
n = obj.N;
if(obj.dim == 2)
X = obj.Support.unifGrid([n,n]);
xplot = X(1,:,1);
imagesc(xplot,xplot,obj.Eval);set(gca,'YDir','normal');axis image;
elseif(obj.dim == 3)
fprintf('Plotting 3D Isosurface...this may t... |
function [classifier, err_count, run_time, mistakes, mistakes_idx, SVs, TMs] = HomOTL2_K_M(Y, K1, K2, options, id_list,classifier)
% HomOTL2: HomOTL-II
%--------------------------------------------------------------------------
% Input:
% Y: the vector of lables
% K: precomputed kernel for all ... |
% This is material illustrating the methods from the book
% Financial Modelling - Theory, Implementation and Practice with Matlab
% source
% Wiley Finance Series
% ISBN 978-0-470-74489-5
%
% Date: 02.05.2012
%
% Authors: Joerg Kienitz
% Daniel Wetterau
%
% Please send comments, suggestions, bugs,... |
function [P2final] = Pdepthtest(P2E, K, x1,x2)
xtestpoint1 = x1(:,1);
xtestpoint2 = x2(:,1);
P1 = [eye(3),zeros(3,1)];
P1K = K*P1;
xhat1 = inv(K)*xtestpoint1;
X = zeros(4,4);
Depth = zeros(4,2);
for i=1:4
xhat2 = inv(K)*xtestpoint2;
A = [P1(3,:).*xhat1(1,1)-P1(1,:);... |
function Comprobar(hemi);
%% Comprobar si los datos estan corregidos correctamente.
%%
hemi = 'lh';
% %filter = '.pial';
%afilter = '.aparc.annot';
estnumber = ['-1'];
InputDir = '/media/Data/ibas/Compatibilidad_Proyecto_PEPs/Procesamiento_FreeSurfer';
mkdir('/media/Data/ibas/Compatibilidad_Proyecto_PEPs/Procesamiento_... |
clear all
fig = openfig('series_series_simulation_detailed.fig');
axObjs = fig.Children;
dataObjs = axObjs.Children;
x_fig = dataObjs(1).XData;
y_fig = dataObjs(1).YData;
z_fig = dataObjs(1).ZData;
Mx=y_fig(:,1);
fx=x_fig(1,:)*150e3;
z_fig(:,19)=z_fig(:,18);
z_fig(:,20)=(z_fig(:,18)+z_fig(:,23))/2;
z_fig(:,21)=(z_fig(... |
function visualize_map(map,path)
%This function visualizes the 2D grid map
%consist of obstacles/start point/target point/optimal path.
% obstacles
for obs_cnt = 2: size(map, 1) - 1
scatter(map(obs_cnt, 1)-0.5,map(obs_cnt, 2)-0.5,250,155,'filled');
hold on;
grid on;
%g... |
% ODE_01.m
clear
close all
clc
tMin = 0;
tMax = 10;
tSpan = [tMin tMax];
y0 = [1,0];
m = 2;
b = 0.2;
k = 3;
K = [m b k];
[t,sol] = ode45(@(t,y) FNT(t,y,K),tSpan,[y0]);
y = sol(:,1);
%dTdt = sol(:,2);
figure(1)
xP = t; yP = y;
plot(xP,yP)
grid on; box on
xlabel('t')
ylabel('... |
function r = dot_product(x,y,z,i1,j1,i2,j2)
r = x(i1,j1)*x(i2,j2) + y(i1,j1)*y(i2,j2) + z(i1,j1)*z(i2,j2);
end |
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