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function verify_cl_stability(system, realization, xsize, c_mode, varargin)
%
% Checks robust stability property violation for closed-loop digital systems using a bounded model checking tool.
% Function: VERIFY_CL_STABILITY(system, realization, xsize, c_mode)
%
% Where
% system: represents a struct with digital system... |
function [ output_args ] = TestTest( input_args )
%TESTTEST Summary of this function goes here
% Detailed explanation goes here
clc;
ws = load ('classes2.mat');
class1 = ws.class1;
class2 = ws.class2;
pr = 2;
% Amain(class1, class2, pr) % 68.5000 18.0000 45.0000
global w;
plot(class1(:,1),class1(:,2),'ro',class2(... |
clc
clear all
close all
%% Read files
[LabelTrain FeatureVectorTrain] = svmlread('books.train');
[LabelTest FeatureVectorTest] = svmlread('books.test');
LabelAssigned = -1*ones(size(LabelTest));
%% Pre-compute Norms for every vector
NormTrain = zeros(1,length(FeatureVectorTrain(:,1)));
NormTest = zeros(1,length(Feat... |
classdef Archive < handle
properties
dim = 1; % dimension of the input space X (determined from x_mean)
X = []; % archive - input-space data
y = []; % archive - dependent-space data
gens = []; % archive - generations of the data where they come from
tolX... |
function ulti_ErrGradDec(ang_X,ang_Y,nr)
%Michael Williams 2015, Email:michael.williams.hy@gmail.com
%I use the gradient decrease method to find the proper step lenth for the X
%axis rotation and the Y axis rotation
format compact
clc
tic
numStep=100000; %prelocating of numStep to increase the speed
rads = [10,13,17,2... |
function [img_skel, branch_pts_image, labeled_vess_segs, vess_radius, binary_hs_image, hotspots_pts_image_dil, results_table_um_new_table, hs_diameter_table] = vessel_ntec_analysis_func(vessels_seg, dapi_img, particles, px_per_um, save_dir,sample_name)
tic
shortfile = sample_name;
display(['Analyzing vessels for ' s... |
function [ mass_assem, stif_assem] = be_beam_fe( n, m, ei, l, alpha )
me = m/n;
le = l/n;
[ mass_matr, stif_matr] = be_beam_matr( me, ei, le, alpha );
mass_assem_temp = zeros(2 * n + 2, 2 * n + 2);
stif_assem_temp = zeros(2 * n + 2, 2 * n + 2);
for j = 1:n
mass_assem_temp(2 * j - 1 : 2 * j + 2, 2 * j - 1 : 2 * j... |
function [x,n] = zeropad(x,n,N)
if(min(N)<min(n))
for i = min(N):min(n)-1
x = [0 x];
end
else
for i = min(n):min(N)-1
x(1) = [];
end
end
if(max(n)<max(N))
for i = max(n):max(N)-1
x = [x 0];
end
else
for i=max(N):max(n)-1
x(length(x)) =[];
end
end
n = N
end |
function [xhist, Phist] = mekf(x0, P0, W, V, rN, whist, yhist, dt)
xhist = zeros(7,size(yhist,2));
xhist(:,1) = x0;
Phist = zeros(6,6,size(yhist,2));
Phist(:,:,1) = P0;
for k = 1:(size(yhist,2)-1)
[xp, A] = prediction(xhist(:,k),whist(:,k),dt);
P_p = A*Phist(:,:,k)*A' + W;
[yp, C] = measurement(xp(1:... |
clear, clc, clf
%load('threes.mat')
load threes -ascii
%% Construct the mean three
clc, clf
colormap('gray')
three_mean = mean(threes, 1)
imagesc(reshape(three_mean,16,16),[0,1])
%% Plot eigen values
mean_vector = mean(threes, 2)';
threes_zero_mean = threes' - mean_vector;
covariance_matrix = cov(threes... |
% This script analysis the relation between blocklength , power allocation
% coefficient and user 2 distance under different power
% calculate blocklength and power allocation coefficient according
% different conditon
clc; clear variables; close all;
N = 1e6;
N1 = 80;
N2 = 80;
eplsion1R = 10^-5;
eplsion2R = 10^-4;
... |
function [trcfiles,dwtfiles] = findTracesDwt( filenames )
% FINDTRACESDWT Look for .traces and .dwt files associated with input files
%% Process input arguments
narginchk(1,2);
if ischar(filenames),
filenames={filenames};
end
%%
trcfiles = cell(size(filenames));
dwtfiles = cell(size(filenames));
for i=1:num... |
% Start EEGLAB
[ALLEEG EEG CURRENTSET ALLCOM] = eeglab;
% Replace this fields with your path and filenames
datapath = '/home/mdynamics/Desktop/noahSPROJ_participants/5/uncut/';
datafilename = '5_uncut.edf';
datafile2save = 'test_export.edf';
% Import EDF using BIOSIG
EEG = pop_biosig([datapath datafilename]);
% Wri... |
function main()
addpath('~/asigDSIC/ETSINF/apr/p2/BNT')
addpath(genpathKPM('~/asigDSIC/ETSINF/apr/p2/BNT'))
for g=[1,2,4,8,16]
out = sprintf('Numero de Gaussianas: %d',g);
disp(out);
for i=[1,2,4,8,16]
out = sprintf('Numero de iteraciones: %d',i);
disp(out);
... |
%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
% DRIVER ROUTINE FOR THE B5200 EQUATION.
% WITH F, MAS AND PDERV TO BE SAVED AS !SEPARATE! M-FILES.
% AUGUST 2005.
%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
function B5200
global MYtagSTIFF
MYtagSTIFF = 1;
... |
clc
clear
load('AdjustedCRNH02032016GANewton8W.mat')
DataTable=CRNH02032016GANewton8W;
clear AdjustedCRNH02032016GANewton8W
ts = length(DataTable.LocalDay);
sampleSizes = zeros(12,1);
[prevMonth,prevDay] = convertDate(DataTable.LocalDay(1));
allpoints = zeros(365,24);
seasonlabels{365} = [];
% seasonlabels = zeros(1,3... |
%Surface plot 3d
[X,Y] = meshgrid(1:0.5:10,1:20);
Z = sin(X) + cos(Y);
surf(X,Y,Z)
%phase one
[X,Y] = meshgrid(1:0.5:10,1:20);
Z = sin(X) + cos(Y);
C = X.*Y;
surf(X,Y,Z,C)
colorbar
%phase 2
[X,Y,Z] = peaks(25);
CO(:,:,1) = zeros(25); % red
CO(:,:,2) = ones(25).*linspace(0.5,0.6,25); % green
CO(:,:,3) = ones(25).*... |
function [C, sigma] = dataset3Params(X, y, Xval, yval)
%EX6PARAMS returns your choice of C and sigma for Part 3 of the exercise
%where you select the optimal (C, sigma) learning parameters to use for SVM
%with RBF kernel
% [C, sigma] = EX6PARAMS(X, y, Xval, yval) returns your choice of C and
% sigma. You should co... |
function y = CEC2020_functions(x)
global fun_num;
y = feval(@cec20_func, x', fun_num);
end |
maxTime = [];
for ii=1:size(alltpAll,2)
maxTime(end+1) = alltpAll(ii).maxTime;
end
maxTime = reshape(maxTime, lp.dims(2),lp.dims(1))'
figure;
imagesc(maxTime); |
function Sigma_Vector=alpha_generator(l,M,nk)
if l==0 || l>M-1 || nk>M
display('wrong input parameter')
Sigma_Vector=[];
return
end
flag_one=0;
for k=1:nk-1
temp(k)=exp(j*2*pi*k/nk);
if temp(k)==exp(j*2*pi*l/M)
flag_one=1;
end
end
if flag_one... |
//
// Game.m
// MoonHerder
//
// Created by Roger Engelbert on 10/9/12.
// Copyright Done With Computers 2012. All rights reserved.
//
#import "Game.h"
// Game implementation
@implementation Game
@synthesize screen = _screen;
@synthesize sounds= _sounds;
@synthesize images = _images;
@synthesize gameData = _gam... |
clear;clc;
syms q1 q2 o_x o_y o_theta dq1 dq2 do_x do_y do_theta ddq1 ddq2 ddo_x ddo_y ddo_theta real
syms m_l L I_l w m_o I_o g real
syms tau_1 tau_2 real
theta = [q1;q2];
dtheta = [dq1;dq2];
ddtheta = [ddq1;ddq2];
x = [o_x; o_y; o_theta];
dx = [do_x; do_y; do_theta];
ddx = [ddo_x; ddo_y; ddo_theta];
% Local coord... |
function ring=atsetshift(varargin)
%ATSETSHIFT sets the misalignment vectors
%
% RING=ATSETSHIFT(RING, ELEMINDEX, DX, DY) sets the entrance and exit misalignment vectors
% of one element or a group of elements in the globally defined lattice THERING.
%
% ELEMINDEX contains indexes of elements to be misaligned
% DX, DY... |
function init_lgear
global Lgear
global Geom
NN=2;
% Main Gear Parameters
%--------------------------------------------------------------------
% Local Parameters:
%--------------------------------------------------------------------
xpos = Geom.Wing.xwac + (6.05*0.3048 - 0.25*2.865); % X pos of... |
function [q_right, q_left] = move_legs (Ts, T_tot, q0_right, q0_left)
Tss = 1.5; %time for the step in single support
Tds=1;
Tstop=1.5;
T = 2*(Tss+Tds);
% step conditions
L = 0.07; %step length
%************************************
% double support phase on right leg *
%**********... |
% MOROZOV(A, M, DELTA, INIT_GUESS)
% Calculates the alpha parameter using Morozov's discrepancy principle.
% Parameters:
% - A = the filter matrix from the matrix model
% - M = measurement data
% - DELTA = approximation of the level of noise in measurement data
% - INIT_GUESS = initial guess of the alpha parameter
%
% ... |
clear all
n = 10;
M = [1:n]';
I = (2:n);
tic;
N = cumsum(M(I),'reverse')';
toc
tic;
sum(triu(ones(length(I)),0).*M(I)',2)';
toc
tic;
sum(triu(repmat(M(I)',length(I),1)),2);
toc |
%% Esempi di errore
figure(1)
img_nprocs = imread('errore_nprocs.png');
image(img_nprocs)
title('Errore: numero di processori non positivo');
figure(2)
img_dim_int = imread('errore_dim_non_intere.png');
image(img_dim_int)
title('Errore: le dimensioni devono essere valori interi');
figure(3)
img_dim_neg = imread('erro... |
model = createpde;
importGeometry(model,'Torus.stl');
pdegplot(model,'FaceLabels','on') |
% PART A | Initiation
clear all; close all; clc
exlPath = 'D:\UMD\764 Quantitative Investment Strategy\Matlab Exercises';
exlFileListInSample =...
{'lab5_data_2003_2004.xlsx', 'lab5_data_2004_2005.xlsx',...
'lab5_data_2005_2006.xlsx', 'lab5_data_2006_2007.xlsx','lab5_data_2007_2008.xlsx'};
exlFileListOutOfS... |
function fx = example6_2_9_2(OutTol,InTol)
%OutTol 外层dblquad精度
%IntTol 内层dblquad精度
m = 1;
n = 1;
a = 1;
b = 1;
km = 2 * m * pi/a;
kn = 2 * n * pi/b;
function z = Tf_Integrand(u,v)
f_rel = @(x,y)(1 - cos(km * x)).* (1-cos(kn * y)).* cos(u.* x + v.* y);
f_img = @(x,y)(1 - cos(kn * x)).* (1-cos(kn * y... |
%%% Stochastic runs calculating extinction times for the SEIR model with
%%% a varying level of disease induced mortality alpha for fixed
%%% other parameters \gamma, \beta_F and \beta_D
%%% Both population extinction and disease extinction are considered
%%% In all scenarios an outbreak, defined as the susceptible p... |
function [y_cp] = SpanLoading(l_s, l_t, CL, geo, panel)
%Determine center of pressure and spanwise loading
%due to bound vortices and trailing vortices.
BV = [panel.BV];
BV1 = [panel.BV1];
s = [panel.s]';
y_cp.alpha = sum([l_s.alpha].*BV(2,:)' + [l_t.alpha].*BV1(2,:)')/(0.5*CL.alpha*0.5*geo.b); %Eqn 35 in N... |
% function ndhist
% (MEX FILE)
% H = ndhist(S,bins,mins,maxs)
%
% inputs:
% S -- nD x nSamples matrix of elements to be histogramed
% bins -- nD x 1 vector of # bins for each dimension
% mins -- nD x 1 vector of min values for each dimension
% maxs -- nD x 1 vector of max values for each dimension
%
% H -- n... |
%sc50 -1st Line of script sc50
clc
clear all
N = 100;
kr = 16;
k1=[0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15];
pr=[0.3028 0.21 0.147 0.1029 0.072 0.0504 0.0352 0.0247 0.0172 0.0121 0.0084 0.0059 0.0041 0.0029 0.002 0.0014];
xd(1:N)=0;
for k=1:N
xd(k)=gen57(k1,pr);
end
%матожидание заданной СВ
m = 0;
for i=1:kr
m =... |
function [F] = pFlux(u,V0,a)
% Calculates the flux vector for a system of nonlinear advection
% equations in polydisperse sedimentation
%
% [F] = pFlux(u,a)
%
% F: calculated flux
% u: states vector of dispersed phases
% V0: relative velocity law constant
% a: exponents vector
%... |
% Funkcja Rungego
f = @(x) (1)./(x.^2+1);
% I jej pochodna (taką mam nadzieję...)
fd = @(x) (2).*x./(x.^2+1)./(x.^2+1);
% Zakres, do którego należy n
Z = 1:10;
E = [];
Es = 1;
for n = Z
% Liczba próbek wynosi 2^n
N = 2^n;
X = linspace(-5, 5, N);
Y = f(X);
Yd = fd(X);
pp = hspline(X, Y,... |
function M = get_M_flag( R_rho, R_th, h0, nel, nb, parms )
%Builds the mass matrix for the DIMENSIONLESS system of equations.
%The dimensional form has a factor rho*A that pre-multiplies the matrix,
%where rho is the mass per unit volume and A is the cross sectional area.
%In the dimensionless form of the equations,... |
function sOut = makeHtmlTable(M, T, rowNames, colHeaders, colors, strPrecision)
%MAKEHTMLTABLE Display matrix contents as an HTML table
% makeHtmlTable(M) where M is an array
% makeHtmlTable(M, T) where T is a cell array of strings equal in size
% to M. The contents of T are displayed preferentially when T i... |
path_arr = strsplit(mfilename('fullpath'), {'/', '\'});
path_arr(end) = [];
base_path = strjoin(path_arr, '/');
addpath(base_path + "/robot/");
|
function symbol = detect_symbol(mask)
% Devuelve la forma de las figuras de cada carta.
% Calculamos las distintas componentes conexas de la m�scara y las
CC = bwconncomp(mask);
labels = labelmatrix(CC);
% Proporciona el grado de inclinacion de la componentes conexas con
% respecto a la horiz... |
%=========================================================================
%
% Empirical power of the Breitung test
%
%=========================================================================
clear all
clc
% Parameters
t = 1000;
cv = [0,-5,-10,-15,-20];
reps = 100000;
tdf = zeros(reps,length(cv));
rho = zero... |
function f_disprof_clustPlot(result,txt,top,scale)
% - plot dendrogram of a DISPROF-based custer analysis
%
% USAGE: f_disprof_clustPlot(result,txt,top,scale);
%
% result = structure of results obtained from 'f_disprof_clust' function
% txt = cell array of row labels, if empty autocreate
% e.g., txt = {'A' ... |
function [ kl ] = kl( p, q )
%KL calculates Kullback-Leibler divergence for given input densities
if isstruct(p); p = p.z; end
if isstruct(q); q = q.z; end
p = p ./ sum(p(:));
q = q ./ sum(q(:));
assert( all( p(:) >= 0 ) );
assert( all( q(:) >= 0 ) );
kl = p .* log(p./q);
kl(isnan(kl))=0;
if any(isinf(kl(:)))
%warni... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Created: 04-Apr-2014 16:53:06
% Computer: GLNX86
% Matlab: 7.9
% Author: NK
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% integrates over depth to calculate
% -Brunt Väisälä frequency
% -Rossby Radius
% -Rossby wave first baroclinic phase speed
% TODO redo ALL !!!
function S01b_fromRaw... |
%Name: David George
%StudentID: 251004930
T = input_data();
%Part A)
ans = var_prob(T, 'npreg', 2);
disp(ans);
%Part B)
compareFigure(T);
%Part C)
D = table2array(rmmissing(T(:,[1:6])));
D = squareform(pdist(D));
%Classical MDS
MDS = cmdscale(D, 2);... |
function [ w ] = weight_update( X, w, mu )
%WEIGHT_UPDATE Update weights using gradient ascent.
% The ascent step is given by solving for the gradients of
% F[w] = 1/n * \sum_i w_i + \sum_i \int_{V_i} |x_i - x|^2 - w_i d\mu
%
% Explicitly, we can compute
% dF/dw_i = 1/n - \int_{V_i} d\mu
% which leads t... |
load 'file'
N_hidden = 12;
learningrate = 0.0015;
iter = 300;
A = imread('image.jpg');
row =
col =
A = A(row,col,:);
imshow(A);
A = rgb2gray(A);
A = resize(A, [16 16]);
A = double(abs(A-255)/255);
A = A';
A = reshape(A, [1 256]);
[percenterror W_1 W_2] = ANNRun(N_hidden,learningrate,iter);
[neg_loglike,output_y] =... |
clc
clear
csi_trace=read_bf_file('G:\无源感知研究\数据采集\2019_04_02\sample_2_1.dat');
L=length(csi_trace);
amplitudeA=zeros(L,30);
amplitudeB=zeros(L,30);
amplitudeC=zeros(L,30);
phaseA=zeros(L,30);
phaseB=zeros(L,30);
phaseC=zeros(L,30);
for m=1:L
csi_entry=csi_trace{m};
csi=get_scaled_csi(csi_entry);
%csi1=... |
function [corr_reg,mse_reg] = CreateScatter(bctarget,target,output,flagRegioMat,iSc,nx,ny,nomeDir,aqi,absdel)
%independent scenario validation scatter
%create scatter for abs and delta values
nameFile={'absValScatter-sce-n','delValScatter-sce-n'};
if absdel==0
scatterTarget={'target','bctarget-target'};
scatte... |
function out=jdDpxExpHalfDomeRdkAnalysisSpeed_LK_NoPool_unlim_deltaFF_opt2(files,option,gainOrYaw,phiOrIhp)
% Analyze halfdome mouse on ball data
% see also:
% jdDpxExpHalfDomeRdkAnalysisSpeedSlidWin
% jdDpxExpHalfDomeRdkAnalysisSpeedEarlyLate
%
if ~any(strcmpi(gainOrYaw,{'gain',... |
function clearKeyboard
% clear keyboard buffer
%% prepare keyboard
while KbCheck; end |
function [ti, seq, exitflag] = detectStructure(tout, nu)
% ok if exitflag = 1
ti = [];
seq = [];
exitflag = -1;
LW = 1.5;
axisColor = 'k--';
fini = 0;
while(fini==0)
fini = 1;
textt = ['Click on the figure to give the structure (press enter when it is done): all time... |
clear;
importfile('Falmouth2004.dat');
% Choose proper wind speed data from all data set
speed=data(51:800,1);
speed=speed';
% use autoregressive
train=speed(1,1:500);
forpredict=speed(1,501:700);
RMSE=zeros(1,11);
MAPE=zeros(1,11);
for i=2:12
model= ar(train,i);
[m,n]=size(model.a);
coef=zeros(m,n-1);
for p=2:n
... |
function [model] = softmaxClassifierL1(X,y,lambda)
% Compute sizes
[n,d] = size(X);
k = max(y);
W = zeros(d,k); % Each column is a classifier
[W(:) ] = proxGradL1(@softmaxLoss,W(:),lambda,500,X,y,k);
model.W = W;
model.predict = @predict;
end
function [yhat] = predict(model,X)
W = model.W;
[~,yhat] = max(X*W,[],2);
... |
x=0:pi/180:2*pi;
for i=1:20,
phi=2*pi/20*i;
plot(x,sin(x+phi));
drawnow;
M(i)=getindexedframe;
end;
aviwrite('sinewavemovie.avi',M,4); |
function A = gs3_readstatus(serobj)
%A = GS3_READSTATUS(SEROBJ);
%
% gets the GS3 multiplexer status
%
%--------------------------------------------------------------------------
%--------------------------------------------------------------------------
% Sharad J. Shanbhag
% sshanbha@aecom.yu.edu
%--------... |
function [cv_abs_err, train_abs_err] = svr_exclude_feat(train, cv, exclude)
train_inputs = train(:, 1:9);
cv_inputs = cv(:, 1:9);
train_m = size(train_inputs, 1);
cv_m = size(cv_inputs, 1);
train_y = train(:, 10);
cv_y = cv(:, 10);
train_reduced_X = reduced_features(tra... |
clear all
clc
%% outline %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
load Mat_en_XP_anntest.mat
re=dat_En_pr;
si=out_si_pr_en_new;
ind=find(abs(si-re)>0.01);
h=fun_plot_res_sqr(re,si,['pr 17-60 rand 10000']);
hold on
plot(re(ind),si(ind),'ro')
% fi_na=['../imgs/en/10en_atom_dis_anntest/cong... |
function feature = tumour_histogram(tumour)
tumour_h = reshape(tumour, numel(tumour), 1);%%将肿瘤图像拉伸为一维向量
k = 1;
for i = 1:length(tumour_h)
if tumour_h(i) ~=0
tumour_adjust(k) = tumour_h(i);
k = k+1;
end
end
%% 常规参数计算
tmax = max(tumour_adjust); %%最大值
tmin = min(tumour_adjust); %%最小值
tmean = mean(t... |
classdef ClassificationTree < ...
classreg.learning.classif.FullClassificationModel & classreg.learning.classif.CompactClassificationTree
methods(Hidden)
function this = ClassificationTree(X,Y,W,modelParams,...
dataSummary,classSummary,scoreTransform)
if nargin~=... |
% function [imdb] = mining_tuples(imdb_in,total_fea,bthid,opts)
% imdb = gen_tuples(imdb_in,total_fea,bthid,opts);
% end
function imdb = gen_tuples(imdb_in,total_fea,bthid,opts)
mode = opts.mode;
mining_per_batch_num = opts.mining_per_batch_num;
batchsize = opts.batchsize;
neg_num = opts.neg_num;
... |
% summarize Sumarize object contents
%
% This method summarizes the contents of a group.
% >> summarize(group); % results printed to command window
% >> name=summarize(group); % object names returned as an output
%
% See also BoundingCurveGroup, view
%
%
% created December 15, 2014 by Daniel Dolan (Sandia Na... |
function replan = safety_entrance(replan, i)
global robot zone total_path_len
zone_diff = robot(i).next_zone - robot(i).cur_zone;
% [-1,0], up
% [1, 0], down
% [0, 1], right
% [0, -1], left
all_cur_pos = cellfun(@(x)x(1,:),{robot(zone(robot(i).next_zone(1),robot(i).next_zone(2)).robot).path},'un',0);
all_cur_pos = re... |
function [y]=fun(k,x)
A=k(1);
t2=k(2);
y=(A).*(exp(-x./t2));
% y=(A).*(exp(-x./t2)); |
%% Research Topic : Modeling multilayer Building Envelopes
%% Author : Sajith Wijesuriya, Nick Kincaid, Paulo Tabares
%% Institution : Department of Mechanical Engineering, Colorado School of Mines
%% Research Group : Dr. Tabares Research Group
%% File Feature : Discreetization intended fo... |
function qsm_7T_bipolar(path_mag, path_pha, path_out, options)
% Re-define the following default settings if necessary
%
% PATH_DICOM - directory for input GE dicoms
% PATH_OUT - directory to save nifti and/or matrixes : QSM_SPGR_GE
% OPTIONS - parameter structure including fields below
% .read... |
function p = OutputPath(R)
%% 输出路径函数
% 输入：R 路径
R = [R,R(1)];
N = length(R);
p = num2str(R(1));
for i = 2:N
p = [p,'—>',num2str(R(i))];
end
disp(p) |
clc
clear all
eps = 1; % Погрешность
etl = 100; % Конец отсчета
% Синусоидальный сигнал
mPi = 2.5;
f = 20; % Частота
f0 = 7; % Сдвиг (фаза)
t = 0:eps:etl;
s = 5 * sin(2 * mPi * f * t + f0); % Амплитуда 7
figure;... |
function T67=T67(h)
T67=-1.96e-3*h+373.2;
|
function portfTWR = calculatePortfTWR(PnlTable, totPnl0, ...
tableAcc, dividendsTable, varargin)
% this function calculate the TWR of the portfolio
% input:
% PnlTable = each asset pnl
% totPnl0 = total value invested
% tableAcc = historical purchases
% dividendsTable = table with all dividends
% varargin... |
%Compute properties for parabolic cylinder coordinates
clear all; syms u v p real
X=[u*v*cos(p); u*v*sin(p); (u^2-v^2)/2];
J=[diff(X,u),diff(X,v),diff(X,p)];
bco=J; bcn=simple(inv(J).');
gco=simple(J.'*J); gcn=simple(inv(gco));
h=sym(zeros(3,3)); cs1=h; cs2=h;
h(:,:,1)=diff(J,u); h(:,:,2)=diff(J,v); h(:,:,3)=dif... |
% book : Signals and Systems Laboratory with MATLAB
% authors : Alex Palamides & Anastasia Veloni
%
%
%
% Problem 8- Discrete time system
% a)delay of two units
num=[1 0 0];
den=[1 .2 .01];
Ts=0.1;
H1=tf(num,den,Ts);
H2=tf(num,den,Ts,'inputdelay',2)
% b)impulse response of H1(s)
n=0:8;
h=dimpu... |
clear; clc
globalVariables
rng(seed);
load(strcat(data_dir, 'train_dataset.mat'))
data = cell(0);
label = [];
counter = 0;
for i = 1:length(data_set)
d = data_set{i};
img = imread([data_dir d.name]);
f_bs_len = length(d.false_bs);
for j = 1:length(d.bs)
counter = counter + 1;
... |
function [s_val, s_time] = calculate_settling_values_f(time, func)
s_val = func(end);
s_time = time(end);
for ii = length(time):-1:1
if ( abs(func(ii) - func(end)) >= func(end) * 0.05 )
s_time = time(ii+1);
s_val = func(ii);
break;
end
end
end
|
% book : Signals and Systems Laboratory with MATLAB
% authors : Alex Palamides & Anastasia Veloni
%
%
% Frequency Response of a system described by the impulse response
% h(t)=exp(-t)u(t)
syms t w
h=exp(-t) *heaviside(t)
H=fourier(h,w)
w1=0:.1:10;
HH=subs(H,w,w1);
plot(w1,abs(HH));
title ('Frequency r... |
Img=imread('test.jpg');
imgsize=size(Img);
subimg_width=round(imgsize(1)/2);
subimg_height=round(imgsize(2)/2);
num_width_spilt=ceil(imgsize(1)/subimg_width);
num_height_spilt=ceil(imgsize(2)/subimg_height);
num=num_width_spilt*num_height_spilt;
for i=1:num_width_spilt
for j=1:num_height_spilt
if(i*su... |
%% Random indoor environment generator
% This matlab script makes random environments within a given boundaries of
% an environment. The corridors are generated by virtual agents, started from
% each location that the robot in the final environment will start from. This
% script ensures that the generated corridors are... |
function succes = infosave(infostr, filename, varargin) %<<<1
% input possibilities:
% infostr, filename
% infostr, filename, autoextension
% infostr, filename, autoextension, overwrite
% check inputs %<<<2
if (nargin<2 || nargin>4)
prin... |
function [q_rid,dist_pt,scales]=build_q_arr(dir,NppEdge)
% build q values for plotting dispersion line on a spagetti plot.
% Inputs:
% dir -- cellarray of 3-vectors, defining spagetti plot ref points
% NppEdge -- number of q-points for each spagetti plot direction
% Outputs:
% q_rid -- cellarray of q-points {qh,qk,ql} ... |
close all
clear all
initialize_folder_names
initialize_TAE_map_calculation_context;
TAE_parameters;
initialize_XZ_maps_dimensions;
rescaling_to_XZsmall_maps;
size_r_TAE=pTAE_sup-pTAE_inf+1
finesse_data_X=reshape((Rpos_PR_map(:,pTAE_inf:pTAE_sup)-R0),NP*size_r_TAE,1);
finesse_data_Z=reshape(Z_PR_map(:,pTAE_inf:pTAE_su... |
function y = reconstructMMSE(xn, tn, t, kernel, reg, eps)
SS = kernel(tsh(tn,tn));
if reg == 1
if eps > 0
c = (SS+eps*eye(length(tn)))\xn;
else
c = pinv(SS)*xn;
end;
else
c = SS\xn;
end;
y = kernel(tsh(tn,t))*c;
|
figure(1); clf; hold on;
%% Using filter
X = [1/2 1 1/2 0 0];
B = [1/4 1/4 1/4];
A = 1;
Y = filter(B, A, X);
N = [0:length(Y)-1];
stem(N, Y, '+');
%% After solving for the impulse response
X = [1/2 1 1/2];
H = [1/4 1/4 1/4];
Y = conv(X, H);
N = [0:length(Y)-1];
stem(N, Y);
|
%script to assemble data for HSMM testing
clear variables;
clc;
%unique ID
ID = 10;
%number of observation symbols
Nobs = 9;
%% ================ INIT PARAMETERS =======================================
%number of hidden states
Nhid = 8;
%max duration
Dmax = 50;
%min duration
Dmin = 1;
[A1_init A_init Afull D_in... |
function [x,y] = measureShift(ixcorr)
% measure the shift of img relative to refImg from xcorr = fft2(img).*conj(fft2(refImg))
sz = size(ixcorr);
assert(length(sz)==2 && all(sz(1:2)>=128 & mod(sz(1:2),2)==0), ...
'image must have even height and width, at least 128 in size')
phase = fftshift(angle(ixcorr));
mag ... |
result_path = 'D:\Documents\University\Year 3\Individual Project\Code\Experiment Setting\Results\ToyData';
for i = 1:10
%% plot for anomalies
true_model = save_model_with_noise(5*i);
path = 'D:\Documents\University\Year 3\Individual Project\Code\';
mtl = MultiTaskLearning('toy_data');
mtl.loadData('... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Basic parameters that may be varied
Ncase = 1; % Forecast case number.
DAYLEN = 1; % Forecast length in days.
DtHours = 1; % Timestep in hours.
%% Indicator for psi-form of equation
StreamFunction = 0;
%%%%%%%%%%... |
function as_stats_barplot_2(mask_stats,P_color)
if ~exist('P_color','var')
P_color = zeros(size(mask_stats,2),3);
P_color(:,3) = [128, 128, 128];
end
figure(1);
cont=0;
for i=1:size(mask_stats,2)
cont=cont+1;
bar(cont,mask_stats(i).axon_diam_mean,'FaceColor',P_color(i,:)/255);
hold... |
function [rbin]=rdfcalc(C,xlim,ylim)
%This file takes a file containing the co-ordinates of the centers as
%input, and finds the rdf
%xlim=512; % The maximum x co-ordinate of the image
%ylim=512; % The maximum y co-ordinate of the image
n=size(C,1);
rmin=1;
rmax=100;
dr=2;
rvecarray=rmin:dr:rmax;
... |
%% init packages
% tick2text
addpath('/home/lab/yuvval/git/tick2text-pkg/tick2text');
addpath('/home/lab/yuvval/git/tick2text-pkg/parsepv');
%% Init path for figs
nowstr = regexprep(datestr(now,0), '-? ?:?', '_');
%figpath = ['/figs/results_' nowstr];
figpath = '~/www/figs/comet/';
overwrite_fig = false;
%%
hdsl_res... |
% testaStruct
carro.fabricante = 'Ford'
carro.potencia = 145
carro.portas = 4
carro.cores = ["amarelo";"azul";"vermelho";"verde";"branco"] |
clc;
clear all;
close all;
o1 = zeros(986, 1606);
o2 = zeros(986, 1606);
o3 = zeros(986, 1606);
filenames = dir('/Users/alex/Desktop/TFM Videos/Sincronizados/Recording 5/Wrapped Images/Camera 1/*.png');
for i = 1:numel(filenames)
image = imread(['/Users/alex/Desktop/TFM Videos/Sincronizados/Recording 5/Wrap... |
clear
clc
close all
disp('Please input n, rho as: [200,0.5]') ;
disp('Feel free to vary nu between 1 and 0 to see the different effects')
disp(' ') ;
para=input('[n, roh]=');
disp(' ');
disp('Please input sig as: [1 0.5; 0.5 1]') ;
disp(' ') ;
sig=input('[sig]=');
n=para(1);
rho=para(2);
[vector,value] =... |
function varargout = DlgPseudo(varargin)
% DLGPSEUDO MATLAB code for DlgPseudo.fig
% DLGPSEUDO, by itself, creates a new DLGPSEUDO or raises the existing
% singleton*.
%
% H = DLGPSEUDO returns the handle to a new DLGPSEUDO or the handle to
% the existing singleton*.
%
% DLGPSEUDO('CALLBACK',hO... |
function entropymeasure = entropyMeasure(dim, r, data, tau, method)
% compute approximate entropy or sample entropy where measure is the method
% used
switch lower(method)
case 'approximateentropy'
entropymeasure = ApEn( dim, r, data, tau );
case 'sampleentropy'
entropymeasure = SampEn( dim, r,... |
dat = readtable("drugs-trial.csv");
dat.id = uint32(dat.id);
dat.age = uint32(dat.age);
dat.type = string(dat.type);
dat.VL = double(dat.VL);
% This creates a viral load measured from the blood sample and makes sense
% of this shit
%a) How many patietns arei in the whole data set
n = length(unique(dat.id));
... |
function c = progprincipal(Ne,fun)
X=feval(@pointmaillage,Ne); %tableau de maillage
% Construction de la matrice M
M=sparse(Ne+1,Ne+1);
for(k=1:Ne)
for(iloc=1:2)
ig = k+iloc-1;
for(jloc=1:2)
jg = k + jloc-1;
M(ig,jg) = M(ig,jg) + simpson('produitphi',X(k),X(k+1),k,iloc,jloc... |
function [ E, t ] = evaluate( Pop )
E = zeros(size(Pop, 1), 1);
for i=1:size(Pop, 1),
s = 0;
t = 0;
for j=1:size(Pop, 2)-1,
for l=j+1:size(Pop, 2),
if Pop(i, j) == Pop(i, l) || Pop(i, j) == Pop(i, l) - (l-j) || Pop(i, j) == (l-j) + Pop(i, l), %linhas e diagonal
... |
%calibrationFunc_hammingLoss_constrScores_numerical numerically computes the calibration function for the Hamming loss on binary variables
% when the scores are oconstrained to be separable (Figure 1a, blue; Proposition 13).
% The formal derivation is provided in Proposition 13: H(eps) = eps^2 /(8 * T), where T is the ... |
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