text stringlengths 8 6.12M |
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function [Yw,Xw,estrho] = myprewhiten(Y,X);
% function [Yw,Xw,estrho] = myprewhiten(Y,X);
%
% Created by Daniel Rowe For Luis Hernandez-Garcia
% seriously by Luis HG for speed.
%
% Prewhiten for AR(1) noise
% Y = n by p data
% X = design matrix n by (q+1)
%
% Yw is new, whitened data
% Xw is new whitened desi... |
function path = lp2(X0, Xf, udata)
% Local planner for 3DOF planar robots
[valid, t0, tf, ...
q_src_0, qp_src_0, q_src_f, qp_src_f, ...
q_sen_0, qp_sen_0, q_sen_f, qp_sen_f] = checkBoundaryConditions(X0, Xf, udata.x_lb, udata.x_ub);
if ( ~valid )
path = struct('xi',[],'ew',[]);
return;
end
... |
clc
clear
close all
%%%%% calculating MSE and PSNR %%%%%
%% W=5,Wsim=3 W=10,Wsim=3:
[MSE1,PSNR1]=PSNR_func(5,3);
[MSE2,PSNR2]=PSNR_func(10,3);
sig = linspace(0.1,1,10);
% base MSE and PSNR:
In=imread('krishna_0_001.png'); % noisy image
Il=imread('krishna.png'); % latent image
In=double(In)/255;
Il=doub... |
function [y] = rsqrt(x, table, num_iter, W, F, Fm)
% disp(horzcat('x: ', num2str(x.double)))
% disp(horzcat('x: ', x.bin))
y0 = computeY0(x, table, W, F, Fm);
% disp(horzcat('y0: ', num2str(y0.double)))
% disp(horzcat('y0: ', y0.bin))
y = newtonIterationBlock(y0, x, num_iter, W, F, Fm);
end |
% XXXXXXXXXXXXXXXXXXXXXXXXXXXX htet_export_results_to_excel_files XXXXXXXXXXXXXXXXXXXXXXXXXXXXX
%
% Author : Htet
% Date : Sep 11, 2019
% Function : export prediction results to excel files
% Syntax : htet_export_results_to_excel_files(SYSTEMS, isLateral)
%
% SYSTEMS - can be either lateral systems ... |
function Jmat = jacFxn(t,Y_in,jacOut,knotSeq,CP,maxT)
NoutCol = bSplineMat_lite(knotSeq,t/maxT,jacOut.orderS);
fluxCombine = jacOut.fluxStoicTode*CP*NoutCol;%%%flux needs int
k = 1./(jacOut.Y2concY*Y_in);
xFract = Y_in.*k;
xCoeff1 = k - Y_in.*k.^2;
xCoeff2 = -xFract(jacOut.yTagBEM_denom).*k(jacOut.yTagBEM_denom);%col2... |
function [r_rmse, g_rmse, b_rmse, rmse] = RootMeanSquareError(image1, image2)
[h1, w1, d1] = size(image1);
[h2, w2, d2] = size(image2);
image1 = double(image1);
image2 = double(image2);
if d1 ~= d2
sprintf("Error: Image color channels are not equal.");
rmse = 0;
... |
%Project by Students:
%
% Παναγιώτης Πράττης / Panagiotis Prattis
%
%Code for:
% Isolate columns, join tables and create a new matrix
% containing the common elements of the u, u1 matrixes
%
u = u(:, [1 2]);
u1 = u1(:, [1 6:24]);
[~, length_i] = ismember(u(:, 2), u1(:, 1));
Matrix = [u, u1(length_i, 2:2... |
function [ newDBN ] = dbninit( dbn, x )
%dbninit initilaze dbn using rbminit
for u = 1 : numel(dbn.sizes) - 1
dbn.rbm{u} = rbminit( dbn.rbm{u}, x );
end
newDBN = dbn;
end
|
%Prob. 6(b)
w = linspace(-3*pi, 3*pi, 61);
Fs1 = 30;
T1 = 1/Fs1;
F1 = linspace(-3/2/T1, 3/2/T1, 61);
X1 = zeros(1, 61);
for N = 1:61
W = (N-31)/10*pi;
for k = -1:1
if (W-2*pi*k)/T1 - 16*pi == 0
X1(N)= X1(N) + 1/T1*4;
elseif (W-2*pi*k)/T1 + 16*pi == 0
X1(N)= X1(N) + 1/T1*2... |
function run_null_lda_cc_sf(measure, varargin)
defaults = struct();
defaults.n_perms = 1;
defaults.p_training = 0.75;
defaults.per_context = true;
defaults.is_drug = false;
defaults.start = 1;
defaults.stop = [];
defaults.analysis_type = 'lda';
defaults.specificity = 'contexts';
defaults.n_trees = 50;
defaults.config ... |
l1 = 10; % length of first arm
l2 = 7; % length of second arm
% l3 = 4;
nr_p = 50;
theta1 = linspace(0, pi/4, nr_p); % all possible theta1 values
theta2 = linspace(0, pi/2, nr_p); % all possible theta2 values
% theta3 = linspace(0, pi/4, nr_p); % all possible theta3 values
[THETA1,THETA2] = meshgrid(theta1,theta2);
... |
function y = sum_of_squares(x1,x2)
y = ((0.75*(x1*x1)) + (2*(x2*x2)));
end |
function plot(obj,key)
[m,rz] = fetchn(vis2p.RFMapRaw(key),'onpoff_rf','rz');
for i = 1:length(m);
im = double(imresize(m{i},1/rz));
[~,X] = max( squeeze(mean(im,3)),[],3);
[~,Y] = max( squeeze(mean(im,4)),[],3);
clf;
% set(gcf,'position',[680 756 660 342])
subplot(2,4,1:3)
imagesc(... |
function [MKT, HML, SMB, VOD, BP, SHELL, GSK, SL] = DatasetHandling()
% Load from Excel
datasheet = 'BookN100.xls';
SMB = dataset('XLSFile', datasheet ,'Sheet','SMB')
file = 'SMBdata.dat';
% Save to matlab dataset
save(file, 'SMB')
% Load from matlab dataset
load(file,'-mat')
MKT = dataset('XLSFile',datash... |
%输入脸部视频
%将人脸视频先定位6个点，再根据6个点每个点分五块皮肤，每块皮肤像素绿色通道取平均得到30段序列，划分训练集与测试集保存
clc
clear
addpath('.\脸部视频')
num=1;
row=1;
face_num=1;
total_face_num=30;%修改总的人脸个数
total_sample_num=30;%y样本
train_sample_num=20 ;
test_sample_num=10;
% data=zeros(total_sample_num*total_face_num,5000);
% train_data=zeros(20*total_fac... |
function wout = wfromdpdt(t, p, ntunits, tskip)
% wout = WFROMDPDT(t, p, ntunits, tskip)
%
% inputs:
% - t: time vector.
% - p: pressure (same length as t).
% - ntunits (optional): normalization to the units.
% - tskip (optional): time difference to disconsider the
% ... |
function result = accfm_pdf_batch(network, distribName, distribParams, number_of_scenarios, settings, output_file)
% batch processing for the AC Cascading Fault Model following a probability
% distribution
% accfm_pdf_batch(network, distribName, distribParams, number_of_scenarios, output_file)
% runs the AC-CFM in... |
function [Ma,Mrb,M] = Stiffness_matrix(p)
%% Mass matrix of the linearized system
% assembles the mass matrix of the linearized system with integrated
% boundary conditions.
M = zeros(2*(p.Xn-1)*(p.Zn-1) + 2*(p.Xn-1));
%% mass matrix for the algae
Ma = zeros((p.Xn-1)*(p.Zn-1));
for j = 1:p.Xn-1 % xi
for i = 1... |
%% Drawing bar plot for manipulability measure scales
% totally 10 steps
red = linspace(1,0,10)';
blue = linspace(0,1,10)';
dum_zeros = zeros(10,1);
rgb_map = [red dum_zeros blue];
% draw plot
fig_total = figure('position', [0, 0, 600, 600]);
x_temp = [1;nan]; % 10 jobs
pos_bar1 = [];
y_temp = [];
% maxium measure... |
function NP_init_directory_structure
% Not intended to be called by the user
% Function that creates the NP folder structure.
main_dir = pwd;
get_dir_for = {
'Anatomy'
'Functionals'
'Stimuli'
'Results'
};
for n = 1:length(get_dir_for)
make_dir = fullfile(main_dir,get_dir_for{n});
... |
clear all;
close all;
clc;
N=16; % numero di punti
l=2; % potenza di partenza
punti=2*ones(1,N);
esponente=linspace(l,N+l-1,N);
punti=punti.^esponente;
% norm2FFT=zeros(1,N);
% norm2DFT=zeros(1,N);
% norma=zeros(1,N);
% for i=1:N
% vettore=rand(1,punti(i));
% norma(i)=norm(vettore);
% FFT... |
function status = myOutputFcn(t,q,flag,params)
if strcmp(flag,'init') && (t(1) == 0)
params.RaRb = [];
end
if ~strcmp(flag,'done') && ~strcmp(flag,'init')
[~, Ra, Rb, zB, yA, zA, yB, Fp ] = dqdt(t, q, params);
fprintf('t=%6.3f s: Ra=%+5.3f N, Rb=%+5.3f N\n',t, Ra, Rb);
end
% continue...
status = 0;
e... |
% LASSO regularization with alpha = 1 which returns fitted least-squares regression coefficients for linear models of
% transcript/flux/transcript+flux data (x) and the growth rates (y) in 12 growth conditions
load('transcripts_subset.mat') % load transcript data corresponding to 12 growth conditions
load('all_atp... |
%{
# subject.Strain
strain_name: varchar(63) # strain name
---
strain_description='': varchar(255) # description
%}
classdef Strain < dj.Lookup
properties
contents = {
'C57BL6/J', ''
}
end
end |
%Calling cos_one() function to generate the required sinusoid
[signal, time] = one_cos(95, 200, pi/5, 0.025);
%CT Plot using plot()
figure;
plot(time, signal, 'k', 'LineWidth', 2);
xlabel('Time Axis (t)', 'FontSize', 12);
ylabel('sin(t)', 'FontSize', 12);
title('Sinusoidal Plot', 'FontSize', 12);
%Vectors output
signa... |
function [ aYield ] = annualYield( nav, period)
% 根据一段时期Period的nav，计算年化yield
% [ aYield ] = AnnualYield( nav, period)
% nav: 净值序列，第一个元素为1
% period可取如下值： d365, d360, d245, w, m, q, y,默认为d365
% 注意，这里在通过nav计算yield的时候，统一采用了离散复利的计算方法
% 也就是说，r=x(end)/x(1)-1
% ------------------
% 唐一鑫，20150510
% 程刚，20150529，加入 period值 'w'
... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Sandeep Manandhar
%% University of Burgundy, France
%% MSCV6
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% inputs
% image
% kernelSize
% deprecating value C; C = mean - threhold
%% output
% threhold image
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function ThresholdImage = localThresh(imag... |
function [ ] = mtf ( input_args )
%Creacion de 4 im?genes por medio de comandos de MATLAB
% El programa crea 4 imagenes utilizando unicamente comandos de Matlab.
% La primera imagen es guardada como "rampa.jpg" la cual representa una
% gradiente de negro a blanco de izquierda a derecha. La segunda imagen
% es... |
function [Cd,S] = Cd3Deploy(h,t)
Cd = .6; %Rocket Cd
S = pi*(2*2.54/100)^2;
if h < 6100/3.2808 %1500 above spaceport ground in m - main deployment
Cd = 1.5;
S = pi*(45*2.54/100)^2;
elseif h < 9100/3.2808 %Drogue deployment in t or h
Cd = 1.5;
... |
function disp_the_size(X)
[r c]=size(X);
disp(r);
disp(c);
end |
function [ AUS6,SPT ] = TAL( SHABR,SDELTA,SHBR,SDTDH0 )
%TAL CALCULATES THE COEFFICIENTS SPT FOR THE POLYNOMIAL
% SUBROUTINE TAL(SHABR,SDELTA,SHBR,SDTDH0,AUS6,SPT)
% CALCULATES THE COEFFICIENTS SPT FOR THE POLYNOMIAL
% Y(X)=1+SPT(1)*X**2+SPT(2)*X**3+SPT(3)*X**4+SPT(4)*X**5
%... |
%changing value of n
n = 5;
%Gaussian
A1 = matgen(n,1);
A2 = matgen(n,10^4);
A3 = matgen(n,10^8);
A4 = matgen(n,10^12);
A5 = matgen(n,10^30);
xtrue = randn(n,1);
b1 = A1*xtrue;
b2 = A2*xtrue;
b3 = A3*xtrue;
b4 = A4*xtrue;
b5 = A5*xtrue;
x1 = A1\b1;
x2 = A2\b2;
x3 = A3\b3;
x4 = A4\b4;
x5 = A5\b5;
rel_err(1) = norm(x1-... |
1;
function ei = solve_marquardt(damper_x, wt_start, hx, ht, t, nth)
global vareps wt_bounds st num_of_dampers n k a l;
alpha = osc_alpha(hx, ht);
beta = osc_beta(hx);
b = osc_b();
c = osc_c(alpha, b);
c_inverted = inv(c);
sweep_side = eye(2);
cTilde = osc_cTilde(alpha, b);
u = osc_y(hx);
v = osc_sec_y... |
close all
clear all
clc
param.alpha_m = 22*1000;
param.beta_m = 13*1000;
param.alpha_h = 0.5*1000;
param.beta_h = 4*1000;
param.alpha_n = 1.5*1000;
param.beta_n = 0.1*1000;
param.alpha_q = 1.5*1000;
param.beta_q = 0.025*1000;
Fs = 50000;
time = 0:1/Fs:0.05;
index_s = zeros(1,length(time));
index_s(0.01*Fs:0.01*Fs+rou... |
%% 1D CNN for distance density classification.
function [neuralNet, opts] = CnnDistanceDensityNetwork(height, width, channels)
InputLayer = imageInputLayer([height,width,channels]);
% Distance density method uses [3, 1] or [5 1]convolutions.
c2 = convolution2dLayer([1 3], 32, 'stride', [1 1]); %F... |
a = 200;
b = 100;
for i=1:10
froma = round(0.03 * a);
fromb = round(0.05 * b);
a = a - froma + fromb;
b = b - fromb + froma;
fprintf('%f\t%f\n', a, b)
end |
function [ tmp ] = unbiasedestimaton_1n( theta, angle )
% Unbaised estimation of angular velocity w_i and oritantion angle_i
% Pass function the value angular velocity and angle and return a value for
% Phi matrix estimation
% Preallocate local variable
tmp = double.empty;
for n = 2:(length(theta))
tmp(n) = (thet... |
function representation_onepath(eddatafile,reflpathsfile,fuente_imagen,num_rayo,plot_source,plot_receive,separacion_point_edges)
[eddatafilepath,eddatafile,fileext] = fileparts(eddatafile);
eddatafile = [eddatafile,fileext];
Filestem = EDB2strpend(eddatafile,'_eddata');
[reflpathsfilepath,reflpathsfile,fileext] = fil... |
function [H_ue, H_in] = gen_quadriga_channel_file(B, nbr_of_RB, nbr_of_ue, nbr_of_in, fname, new_generate) % check if result same
% Example:
% [H_ue, H_in, lay] = gen_quadriga_channel_file(4, 8, 8, 1);
%%%%% CHECK SAVE REQUIRED OR NOT
dir_name = 'ch_files';
if exist('fname', 'var')
... |
function omcompile (filename,modelname,varargin) % Filename des *.mo-files, modellname, libraries, debug
%
% Loads Modelica-File *.mo and compiles Model modelname,
% optionally loads additional libraries such as 'Modelica' or sets debug flag, first all old files
% are deleted. After compilation the *_init.txt file is... |
function [Is] = ver_eq2(I)
l = length(I);
Is = [];
if l > 1,
for i=1:l-1,
aux = I(i);
auxI = I(i+1:end);
el = find(auxI == aux);
if isempty(el),
Is = [Is,aux];
end;
end;
Is = [Is,I(end)];
else,
Is = I;
end
end |
function [ val ] = exp_helper( ksi,sigma,para )
%This exponential function helps to calculate the exponential part of the
%Weibull CDF.
base = para/sigma;
temp = -1.0 * power(base, ksi);
val = exp(temp);
end
|
function [F,u,v,Nu,Nv,Du,Dv]=griddatacyclic(unoneq,vnoneq,Fnoneq,N)
% u must be 2*pi periodic.
% v must be 2*pi/N periodic.
% (unoneq, vnoneq) is the non-equidistant grid on which F is given.
% (u,v) is the equidistant grid generated with ndgrid which to interpolate to.
Nu=size(Fnoneq,1);
Nv=size(Fnoneq,2);
Dv=2*pi/N... |
clear
clc
k1 = 1;
k2 = 1;
Cont_k1 = 10;
Cont_k2 = 10;
beta = 1;
|
load('f9.mat');
f=figure;
labels= {'First Half: Acquisition', 'Second Half: Acquisition', 'First Half: Extinction', 'Second Half: Extinction'}
for i = 1:size(DATA,2)
subplot(2,2,i)
s=scatter(DATA.(i), anx_scores.TraitAnx, 20, [0 0 0], 'MarkerFaceColor', [0.8 0.6 0.1]);
[r,p] = corr(DATA.(i), anx_scores.Trai... |
function createTemporalTPAForBDA(BDA_name, BDA_trials_count, TPA_num_frames, outputfile)
strROI{1} = TPA_RoiManager();
strROI{1}.Name = 'ROI:Z:1:001';
strROI{1}.Data = zeros(TPA_num_frames, 2);
strROI{1}.xyInd = zeros(30, 2);
strShift = zeros(TPA_num_frames, 2);
for index = 1:BDA_trials_cou... |
% test filtering
%
% This script test different configurations of entropy
% filter over a previously calculated entropy vector e0.
% It uses combination of two parameters of the filter:
% Buffer_size and K,
%
% A matrix with the following columns is generated:
%
% BUFFER_SIZE
% K
% TP: True Positive
% FN: False Negati... |
function G = zassenhaus(f,Zx)
% FACTORIZATION IN Z[x] (ZASSENHAUS)
n = length(f) - 1;
if (n == 1)
G = {f};
return;
end
A = max(abs(f));
b = Zx.lc(Zx,f);
B = sqrt(n+1) * 2^n * A * b;
C = (n+1)^(2*n) * A^(2*n-1);
gamma = ceil(2*log2(C));
r = 1;
gcd = 1;
while(isequal(r,0) || ~isequal(gcd,0))
p = primes(2*ga... |
function [Az El] = RaDec2AzEl(Ra,Dec,lat,lon, Mjd_UT1)
% Programed by Darin C. Koblick 01/23/2010
%--------------------------------------------------------------------------
% External Function Call Sequence:
% [Az El] = RaDec2AzEl(0,0,0,-104,'1992/08/20 12:14:00')
%
% Worked Example: pg. 262 Vallado
%[Az El] = RaDec2A... |
function scs = ApplyDetector(Cparams, ii_ims)
sum = 0;
for t=1:Cparams.T
fidx = Cparams.theta(t, 1);
theta = Cparams.theta(t, 2);
parity = Cparams.theta(t, 3);
fx = Cparams.fmat(fidx, :) * ii_ims;
r = Cparams.alphas(t) * ((parity * fx < parity * theta) * 2 - 1);
... |
function value = H(adjI, adjJ, x)
% q-coloring energy function
% colored_graph = G*diag(x); % Row i contains colors of vertices connected to i
% colored_reverse_graph = colored_graph';
%
% slow_value = sum(colored_graph(G) == colored_reverse_graph(G))/2;
% value = 0;
% fo... |
% Author: Eseoghene Okonofua <EseO@Eseoghenes-MacBook-Pro.local>
% Created: 2017-09-25
% Orthonormal-Coordinate-System
% Intput:
% Points:
%[point1x, point1y, point1z]
%[point2x, point2y, point2z]
%[point3x, point3y, point3z]
%Output:
%[base1x, base1y, base1z]
%[base2x, base2y, base2z]
%[base3x, base3y, ... |
axis equal;
hold on;
xlabel('x');
ylabel('y');
zlabel('z');
rotate_x = @(theta)[
1 , 0 , 0 , 0;
0 , cos(theta) , sin(theta) , 0;
0 , -sin(theta) , cos(theta) , 0;
0 , 0 , 0 , 1;
]... |
function out=calc_elevel_conso(dB_SPL)
%out is elevel in a 4 by 16 matrix
p.electrodes=(22:-1:1)';
p.channel_stim_rate=900;
p.reference_SPL_dB = dB_SPL;
p.num_selected=8;
p.Q=20;
p.phase_width = 25*ones(size(p.electrodes));
p.phase_gap = 8;
p.modes = 103;
p.threshold_levels=zeros(size(p.electrodes)); %electro... |
function str = calculate(str)
% This function calculates CALC fields needed for AWG layout.
% SF, January 31, 2006
global alphai;
global lx;
global theta0;
global dl;
global bcoo;
global ji;
p = str.param; %load AWG parameters
str.calc = []; %delete previous AWG calculations
lx = p.Lx; %initializing globals
t... |
%% Electricity usage, Matlab learning
load dataset/electricity.mat
res = usage(:,1);
comm = usage(:,2);
ind = usage(:,3);
yrs = (1991:2013)';
plot(yrs, res, 'b--');
hold on
plot(yrs, comm, 'k:');
plot(yrs, ind, 'm-.');
title('July Electricity Usage');
xlabel('Years');
ylabel('Usage KwH/m');
legend('Residentials', 'Co... |
function [ index ] = quadrant( p )
%QUADRANT индекс квадранта в котором лежит точка
% Функция возвращает индекс квадранта в котором лежит точка. index = 0,
% обозначает что данная точка не подпадает под условия, то есть квадрант
% не определен.
% p - точка начала луча
% index - квадрант
% Zheltov Victo... |
% Function to crop and resize images of caltech 101 dataset to 224*224
% Input:
% caltechPath: path to caltech 101 dataset.
% eg:'SomePath/101_ObjectCategories'
% outPath: path to cropped dataset.
function cropImages(caltechPath, outPath)
if ~exist(outPath,'dir')
cmd = sprintf('mkdir %s', outPath);
... |
clear all
close all
cd(root);
pat = patienten;
cond= {'onset-klein', 'onset-mittel', 'onset-gross'};
med={'ON','OFF'};
for b=1:length(cond);
for c=1:length(med)
images = ffind(['*' cond{b} '*' med{c} '*' '.nii']);
outimage=['contralateral_' cond{b} '_' med{c} '.nii'];
spm_imcalc(images,ou... |
function period = findPeriod(pulse_model)
pm = pulse_model;
pm = smooth(pulse_model);%perform gentle smoothing to eliminate ridges at peaks and troughs
%get max and min values
pmmax = regionalmax(pm);
pmmin = regionalmax(-pm);
max = pm(pmmax);
maxidx = find(pmmax==1);
min = pm(pmmin);
minidx = find(pmmin==1);
%get abs... |
function y = butterworthSmoothing(x,w)
% y = butterworthSmoothing(x,w)
%
% Implements a simple second-order butterworth smoothing filter. The
% boundary conditions are implemented by using a first-order filter, and
% then by using the raw data value at the very edge.
%
% INPUTS:
% x = vector of uniformly spaced data
... |
function K = kernelComponent(freq_grid, var_grid, x, y)
%Given the lists of hyperparameters and the difference matrix, compute all
%the sub kernel matrices and store in a cell.
Q = length(freq_grid);
subKernels = cell(Q,1);
% compute the difference matrix based on x_train
diffMat = diff_mat(x, y);
% constr... |
function [wimg, flag] = quadtobox(img, M, X, Y, f_type)
if nargin<4 f_type = 'bilinear'; end
% Get all points in destination to sample
xy=[X';Y';ones(size(X'))];
% Transform into source
uv = M * xy;
% Remove homogeneous
uv = uv(1:2,:)';
xi = reshape(uv(:,1),numel(uv(:,1)),1); % can be optimized
yi = reshape(uv(:,2)... |
%% test circulant and convolutional algorithms
%% clear everything
close all;
clear;
clc;
% the code used omptoolbox, if you have it already comment this line!!!
addpath([pwd '/omptoolbox']);
%% read input data
images = {'lena512.bmp', 'barb.bmp'};
Y = readImages(images);
disp('Done!');
[p, N] = size(Y);
%% remove ... |
%Density data
L = 400; number = 15000;
beta = 0.5; a=0.1;
Input = zeros(number , L);
Output_q = zeros(number, L);
Output_th = zeros(number,L);
for j= 1 :number
s = -2*rand(L,1)-2*rand; s(1) = -1; s = Flatten_potential(s,L);
A = zeros( L,1) ; B = zeros(L,1); rho =zeros(L,1);psi = zeros(L,1);
K = sqrt(-s);
A(1) = 1... |
%% Factorización de un polinomio en un cuerpo finito parte 1, parte 2, parte 3
%
% SFD: Factorización libre de cuadrados
%
% DDF: Factorización en grados distintos
%
% EDF: Factorización de mismo grado
%
path(path, 'Algorithms');
path(path, 'Classes');
clear
%% $$F_{q}[x] \quad q = 3^{1}$
%% SDF
%
p = 3;
n = 1;
fqx... |
% EJERCICIOS RESUELTOS DE VISIÓN POR COMPUTADOR
% Autores: Gonzalo Pajares y Jesús Manuel de la Cruz
% Copyright RA-MA, 2007
% Ejercicio 8.6: Descripción de contornos, regiones y superficies 3D
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 8.5.4 Regiones: propiedades métricas
%%... |
% do_bst_extract_alpha.m
%% list all the pairs
subj = {'S01';'S02'; % list subj#1 subj#2 in the order of the file
'S03';'S04';
'S05';'S06';
'S07';'S08'; % list subj#1 subj#2 in the order of the file
'S09';'S10';
'S11';'S12';
'S13';'S14'};
nsubj = size(subj,1);
cond = {
'm1SelfSameComp';
... |
function [aGmx_RE,cos_d_ang_RE] =...
RE_Constraints...
(aGmx,G_diag,K,TK,pi2,angPSF_pi2_m,angGmx,sqrt2,m,...
angPSF_m,z_M,cos_d_ang)
%------------------------------------
% Refer to Section 3.1 for details.
%------------------------------------
... |
function X_rand=Sample(map,goal)
% if rand<0.5
% X_rand = rand(1,2) .* size(map); % random sample
% else
% X_rand=goal;
% end
if unifrnd(0,1)<0.5
X_rand(1)= unifrnd(0,1)* size(map,1); % ¾ùÔȲÉÑù
X_rand(2)= unifrnd(0,1)* size(map,2); % random sample
else
X_rand=goal;
end
|
layer_c1_num=20;
layer_s1_num=20;
layer_f1_num=100;
layer_output_num=10;
yita=0.01;
bias_c1=(2*rand(1,20)-ones(1,20))/sqrt(20);
bias_f1=(2*rand(1,100)-ones(1,100))/sqrt(20);
[kernel_c1,kernel_f1]=init_kernel(layer_c1_num,layer_f1_num);
pooling_a=ones(2,2)/4;
weight_f1=(2*rand(20,100)-ones(20,100))/sqrt(20);
weight_outp... |
% PREY ALGORITHM
% LFG
clc, clear all, close all
global M MAXPreyTypes NNeighbors
%% ----------------- Generate data and dissimilarity matrix ---------------
% Generate data
disp('Generating data ...')
ScaleBetween = [-1 1];
[X,labels] = gen_data('gaussian2',ScaleBetween,false);
% Dissimilarity Metri... |
function data = updateMap(data,Hval)
img = getHSVmap(Hval);
set(data.h.SVchooser,'cdata',img);
data.img = img; |
clear ; close all;
clc
img = rgb2gray(imread('/Users/INNOCENTBOY/Downloads/videos/Imageprocessing/week6/original_cameraman.jpg'));
img = im2double(img);
figure; imshow(img);
%1D motion blur
h = zeros(size(img));
s = size(h);
for i = (s(2)/2 - 8) : (s(2)/2 + 8)
h(s(1)/2, i) = 1/16;
end
blurImg = imfilter(img, h... |
function A_sampled = ColumnSelect(A, k , eps)
A_cur =[];
J=[];
C = k*log(k/(eps^2)) ;
%C = k ;
[m,n] = size(A) ;
%[u,sigma , v] = svd(A)
%[W,lambda] = eig(A' * A) ;
%W = W(:, end:-1:1) ;
%lambda = lambda(:, end:-1:1) ;
[UU,SS,W ] = svd(A);
W_top = W(:,1:k) ;
for j = 1:n
pie = norm(... |
function instrlist = management()
%UNTITLED8 此处显示有关此函数的摘要
% 此处显示详细说明
import real_instrument.*
import virual_instrument.*
import instrument.*
idx = [];
InstrInFile = readtable('.\Defaults_para\Defaults_setting\instrlist.txt','Format','%s%s%s%s%s%s','Delimiter','space','ReadVariableNames',0);
InstrInFile = tabl... |
%% Figure for JEF Gaussian line spreads
%
%% Create the scene and initiate the optics
vParams = vernierP;
scene = sceneCreate('vernier','display',vParams);
ieAddObject(scene); sceneWindow;
scene = sceneSet(scene,'fov',1.2);
%%
pupilMM = 3;
zCoefs = wvfLoadThibosVirtualEyes(pupilMM);
zCoefs(5) = 0;
oi = oiCreate('wvf... |
clear
clc
close all
% load results/simulation1/detectorCounts_z0mm.mat
% load results/simulation1/simulationData.mat
load results/detectorCounts_z0mm.mat
load results/simulationData.mat
%Lensmaker
M=1;
f=20;
% d0=lensZ;
% d0=f*(1+1/M);
d0=25;
M=f/(d0-f)
zf=1/(1/f-1/d0);
M=1;
if isinf(zf)
zf=50;
end
%estimate ... |
fprintf("Classification using mnrfit\n")
data = readtable('wine.csv');
data = data.Variables;
y = data(1:end-50,1);
X = data(1:end-50,2:end);
y_val = data(end-49:end,1);
X_val = data(end-49:end,2:end);
B = mnrfit(X,y);
y_pred = mnrval(B,X_val);
[~,I]=max(y_pred, [], 2);
acc = sum(y_val ==I);
acc = acc/length(y_pred);... |
%%%%%%%%%%%%%%%%%%%%%%%%%%
%(c) Ghassan Hamarneh 1999
%%%%%%%%%%%%%%%%%%%%%%%%%%
function W=GetWeights(Xu);
%function W=GetWeights(Xu);
Distances=zeros(size(Xu,1)/2,size(Xu,1)/2,size(Xu,2));
%using 3 dimensional matrix to contain the distances from landmark1(x) to landmark2(y) in a shape(z)
hwtbar = waitbar(0,'Cal... |
function [tfim_ord,idx_tfim,updated_Operators112,updated_OperatorsINEM,updated_Lines112,updated_LinesINEM,UP_FE112,UP_FEINEM,UP_FEINEM112, updated_state_vars, wait_R,End,Start,last,UP_wait_time,UP_wait_time112]=release(Operators112,OperatorsINEM,Lines112,LinesINEM,FE112,FEINEM,FEINEM112,Type, idx, state_vars,tfim_ord,i... |
mdl_eul = rlCModel('JumpModel_Eul.xml');
vis = rlVisualizer('vis', 480, 960);
vis.addModel(mdl_eul);
mdl_eul.forwardPosition;
vis.update;
clear vis; |
function out = yolov4Predict(matFile, image)
%#codegen
% Copyright 2021 The MathWorks, Inc.
% Convert input to dlarray.
dlInput = dlarray(image, 'SSCB');
persistent yolov4Obj;
if isempty(yolov4Obj)
yolov4Obj = coder.loadDeepLearningNetwork(matFile);
end
% Pass input.
out = cell(size(yolov4Obj.OutputNames,2),1);... |
g=zeros(size(a.linear_link_ids)); %green
g(ismember(a.linear_link_ids,a.link_ids_beats(a.good_mainline_mask_beats)))=2; %yellow
g(ismember(a.linear_link_ids,a.knobs.link_ids))=-1; %blue
g(ismember(a.linear_link_ids,a.link_ids_beats(logical(a.good_source_mask_beats+a.good_sink_mask_beats))))=1; %beige
figure
imagesc(g)... |
function all_test
%plot_mesh_test
%block_example
disp('running all tests')
tol = 1e-9;
err=[
check(@adj_mat_test),...
check(@fun2mat_test),...
check(@mlap3z_test),...
check(@adj_test),...
check(@mass_cons_int_test),...
check(@poisson_fft3z_test),...
check(@wind2flux_test),...
check(@mat_... |
function varargout = groupmanager(varargin)
% GROUPMANAGER MATLAB code for groupmanager.fig
% GROUPMANAGER, by itself, creates a new GROUPMANAGER or raises the existing
% singleton*.
%
% H = GROUPMANAGER returns the handle to a new GROUPMANAGER or the handle to
% the existing singleton*.
%
% GR... |
function [ sig1, sig2, sig3 ] = window_frequency( seq )
%The function calculates three arrays based on the given sequence seq,
%which identifies the consecutive window frequencies of the occurences
%of rise fall and level transitions.
sig1 = zeros(length(seq),1);
sig2 = zeros(length(seq),1);
sig3 = zeros(length(seq),1... |
function output=LSTM_output_ff(outputLayer,w_k,b_k,y2)
%×îºóÒ»²ã
T=size(y2,1);
z_k2=y2*w_k+ones(T,1)*b_k;
numClass=size(w_k,2);
switch outputLayer
case{'softmax'}
temp=exp(z_k2-max(z_k2,[],2)*ones(1,numClass));
output=temp./(sum(temp,2)*ones(1,numClass));
otherwise
output=tanh(z_k2);
end |
function [ddq,Fx,Fy] = autoGen_dynamics_minimal(m,g,r,I,slope)
%AUTOGEN_DYNAMICS_MINIMAL
% [DDQ,FX,FY] = AUTOGEN_DYNAMICS_MINIMAL(M,G,R,I,SLOPE)
% This function was generated by the Symbolic Math Toolbox version 6.2.
% 13-Aug-2015 08:53:37
t2 = r.^2;
t3 = m.*t2;
t4 = I+t3;
t5 = 1.0./t4;
t6 = sin(slope);
ddq ... |
function v = clarke(V, Delta, f, fs, phi, N)
A = (sqrt(6)/6) * (V(1)*exp(1i*Delta(1)) + V(2)*exp(1i*Delta(2)) + V(3)*exp(1i*Delta(3)));
B = (sqrt(6)/6) * (V(1)*exp(1i*Delta(1)) + V(2)*exp(-1i*(Delta(2)+(2*pi/3))) + V(3)*exp(-1i*(Delta(3)-(2*pi/3))));
v = A*exp(1i*(2*pi*(f/fs)*(1:N)+phi)) + B*exp(... |
function fimage = regiongrow(I, varargin)
%
% Performing mean_shift operation on image
%
% Usage:
% [output] = edison_wrapper(I, ...)
%
% Inputs:
% I - original image
%
% Allowed parameters:
% 'hi' - hard uphill constraint
% 'lo' - soft uphill constraint
% 'sumlo' - sum of consecutive 'lo' constraints allow... |
function uncommentBlocks(nbBlocks)
h=load_system("MMADC");
for i = 1:nbBlocks
basepath = 'MMADC/Sensing Channel ';
path = append(basepath, num2str(i));
set_param(path,'commented','off')
end
% for i = 1:nbBlocks
% basepath = 'MMADC/LNA ';
% path = append(basepath, num2str(i));
% set_param(path,'... |
% calculate f1a from our spin wave velocity data
function calc_f1a()
addpath /home/sla/he3/he3lib/matlab
pp=0:35;
[p1,cpar1,cpar1e,cper1,cper1e,~,~] =...
textread('DATA_SW_VEL.txt', '%f %f %f %f %f %f %f');
f1a1 = he3_f1a(p1);
cpar1min = cpar1 - cpar1e;
cpar1max = cpar1 + cpar1e;
cper1min = cper1... |
ClearMonomialOrder[];
SetMonomialOrder[{a,b,c,d,e,f,g,h,i,j,k,l,m,n},1];
Iterations=5;
rels={
a**a - a,
a**a**a**a**a**a - g**f,
b**a**a -c
};
|
p=zeros(30,1);p(1)=400;
pa=zeros(30,1);pa(1)=120;
for n=2:30
if(rand(1)<0.35);
p(n)=p(n-1)*(0.9);
pa(n)=pa(n-1)*(0.8);
else
p(n)=p(n-1)*(1.1);
pa(n)=pa(n-1)*(1.2);
end
end
p
pa |
function [Iout] = enhanceContrastLS(Iin,m,c)
Lut = contrast_LS_LUT(m,c);
Iout = intlut(Iin,Lut);
end |
K = 9*10*10*10; # keturzenkliu skaiciu kiekis
K_skirtingais_skaitmenim = 9*9*8*7;
ats1 = K - K_skirtingais_skaitmenim
K_be_7 = 8*9*9*9;
ats2 = K - K_be_7
ats3 = K_be_7
T = 10*10*10; # n( [0;1000) ), intervale imant sveikus skaicius
T_tam_tikroje_pozicijoje_6 = 1*10*10;
ats4 = T_tam_tikroje_pozicijoje_6 * 3
T_be_6 ... |
function out1 = sym_jc_rnd(tauU,tauL,T,state)
% function out1 = sym_jc_rnd(tauU,tauL,T,state)
% This program generates observations from
% a Symmetrised Joe-Clayton (BB7) copula
%
% INPUTS: tauU, a scalar or a Tx1 vector, the upper tail dependence parameter
% tauL, a scalar or a Tx1 vector, the lower tail de... |
% load('twomoons_sk.mat')
load('usps.mat')
k = length(unique(gnd));
n = size(fea, 1);
n_sample = 20;
m = n - n_sample;
sigma = 0.2;
samples = randsample(n, n_sample);
W = EuDist2(fea, fea(samples,:));
W = exp(-W / (2*sigma^2));
% nystrom spectral clustering
A = W(samples, :);
nonsamples = setdiff(1:n, samples);
B = W... |
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