text stringlengths 8 6.12M |
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matrix=zeros(63,7);
a=0.7;
count=0;
for x=1:63
matrix(x,1:6)=binary(x,6);
end
for x=1:63
res=sum(matrix(x,1:6));
modul=mod(res,2);
matrix(x,7)=modul;
end
w_z=-0.5 + 0.5 .*rand(6,6);
w_z_z=-0.5 + 0.5 .*rand(6,6);
w_y=-0.5+ 0.5 .*rand(1,6);
input=zeros(1,6);
hide_la=zeros(1,6);
dz=zeros(1,6);
dzz=zeros(... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Finding Nested Logit FOC Jacobian
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% The calculations of the FOC Jacobian is done on the last period of the
% Painkillers dataset.
% Put shareHessian in Nes... |
function [X] = my_dct2(x)
% Computes the 2-dimensional discrete cosine transform (DCT-II) of matrix x
X = my_dct(my_dct(x).').';
end |
function scores = AttractioNet_objectness_scoring(model, image, bboxes, skip_image_conv_layers)
% AttractioNet_objectness_scoring:
% It implements the objectness scoring module of AttractioNet. The
% objectness scoring module assign confidence score to each input box that
% represents how likely it is each box to tight... |
function xT = findTraj(r, n, m, dim, tDes, posDes)
H_joint = [];
for i=1 : m
% find cost matrix for each segment
H = findCostMatrix(n, r);
% multiply by time factor to nondimensionalize
H = 1 ./ ((tDes(i+1, 1) - tDes(i, 1))^(2*r-1)) .* H;
% put in block diagonal ma... |
% 0NE GENE AUTOREGULATION
% desired behavior only with a hill function with steepness > 2 so that
% once the autoregulation kicks in the activity level converges
clear all;
% constants
TIME_STEP = 0.01;
tmax = 5;
timeArray = 0:TIME_STEP:tmax;
n = length(timeArray);
% network
positive = true;
productionRate_x = 25;
d... |
function [A0 A O] = genHMMparam(A0_hsmm, A_hsmm, O_hsmm)
A0 = A0_hsmm;
A = A_hsmm;
O = O_hsmm;
%data for running murphyk HMM code
save('murphykHMMinit', 'A0', 'A', 'O'); |
function []=saveanimate(filename,pout,vout,uout)
global u_0 h_0
pmin=min(min(pout));
pmax=max(max(pout));
umin=min(min(uout));
umax=max(max(uout));
x=[pmin-10:0.01:pmax+10];
[e,~]=size(pout);
figure;
for i=1:e
p=pout(i,:);
v=vout(i,:);
u=uout(i,:);
%t=tout(i);
[h,~]=Gauss(x,pout(i,:),vout(i... |
% PURPOSE: Generates dummy observations for a Minnesota Prior
% -----------------------------------------------------
% USAGE: vm_dummy
% -----------------------------------------------------
% NOTE: requires to run vm_spec.m
% -----------------------------------------------------
% tau : Overall tightness
% d ... |
%%%%% Test network's performance on the test patterns %%%%%
%sumSqrTestError = 0;
%crossEntError = 0;
%sumOfError = 0;
all_outAct = zeros(size(outAct, 1), size(inputs_test, 2));
inputs_test = test_images;
prediction = zeros(1, 1253);
for pat = 1:size(inputs_test, 2);
%%%%% forward pass %%%%%
... |
function d=getDilatedanmarP2X4sense(y)
d=y(:,7)+y(:,8);
end |
function varargout=roo2brightness(varargin)
%ROO2BRIGHTNESS Convert spectrum to ISO Brightness.
% BRIGHTNESS=ROO2BRIGHTNESS(ROO,WL) with size(ROO)=[M N ... P W] returns
% matrix BRIGHTNESS with size [M N ... P].
%
% ROO holds M*N*...*P spectral readings with W spectral bands and WL,
% size [1 W], holds th... |
function [ t , x ] = sinusoidal_generator( A, f0, fase, FS, Tx )
% Criar o vetor de pontos - grelha de tempo.
t = 0 : 1/FS : Tx;
x = A * cos(2 * pi * f0 * t + fase);
sound(x);
%uncomment in 4c and 4d
%figure;
%plot( t, x);
end
|
% clear variables
%
% % Create Vd and nd for use with karma_sim_jacobian_compare_1cell
% filename = 'data_1cell_b800_18000_Vpert_0p03125'
% eval(['load ' filename '/configinfo']) % load corresponding data
%
% x=floor(perttime/writeint)%9 % Indicate the interval before the one where the perturbation was applied... |
% Program 8.6 Finite element solver for 2D PDE
% with Dirichlet boundary conditions on a rectangle
% Input: rectangle domain [xl,xr]x[yb,yt] with MxN space steps
% Output: matrix w holding solution values
% Example usage: w=poissonfem(0,1,1,2,4,4)
function w=poissonfem(xl,xr,yb,yt,M,N)
f=@(x,y) 0; % define input ... |
%%%%%%%%%%%% CREATE FUNCTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%
% I will be verry quick on this one because it could be usefull not only
% if you alreday manage matlab well
%
% Creating can seems not really usefull at the begging but in fact it same a lot of time
% because you will create the function once and use i... |
close all
clc
N = 5;
robot = Robot();
map = [0,0;60,0;60,45;45,45;45,59;106,59;106,105;0,105];
%% Calibrate
%robot.calibrateTurn(-2*pi, 1)
%% Time rotating scanner
% time = zeros(1,N);
% for i = 1:N
% deg = 360.0 - (360.0 / robot.scan_num);
% % prep motor
% if robot.scan_clockwise
% pow... |
%Computes the equally weighted portfolio analyses results for the Alpha
%analysis and the Recession analysis.
Alleff = load('all_efficient.mat');
eff_inter = mean((Alleff.Alleff_ar1)');
eff_prior = mean((Alleff.Alleff_ar12)');
eff_cross = mean((Alleff.Alleff_cross)');
original = mean((Alleff.excInd)');
PCA = l... |
clear all, clc;
v = rand(7,1);
w = rand(7,1);
z = 0;
for i = 1:7
z = z + v(i) * w(i);
end
z
z1 = sum (v .* w)
z2 = w' * v
% z3 = v * w'
% z4 = w * v' |
function [points,quads,curv] = coregrid(r1)
R_right=[r1/4; r1/2; r1];
theta = 2*pi/4*(0.5:1:3.5)';
% Right shells
shell_right=exp(1i*theta)*R_right';
points=shell_right(:);
% Right and Left shells
q0=[5,1,8,4; 6,2,5,1; 7,3,6,2; 8,4,7,3];
quad_inner=[q0+0;q0+4];
% Core
quad_core=[1,2,4,3];
% Gather all quads
quads=[qu... |
function [ N ] = NURBS_2D(xi_1, xi_2, i_1, i_2, p_1, p_2, n_1, n_2, Xi_1, Xi_2, w)
%compute 2d nurbs basis function
NumKnots_1 = length(Xi_1);
NumKnots_2 = length(Xi_2);
if(NumKnots_1 ~= n_1+p_1+1)
error('n+p+1 is not equal to the number of knots, for dimension 1');
end
if(NumKnots_2 ~= n_2+p_2+1)
... |
clear;
pro_mem_eff;
N=50;
con_e_max=0.2366;
option=gaoptimset('TimeLimit',3600*5,'Display','iter','TolFun',1e-10,'PopulationSize',30,'Generation',100);
lb=[0 0 0];
ub=[100 100 100];
[x fval]=ga(@delta_pid_mppt,3,[],[],[],[],lb,ub,[],option);
dJ=delta_pid_mppt(x);
%save('fuzzy_ga_opt.mat','x')
%}
|
function [predicted_classes,predicted_scores] = predict_Hellinger_forest(model,features)
%Function: predict_Hellinger_forest
%Form: predicted_classes = predict_Hellinger_forest(model,features)
%Description: Predict labels using trained Hellinger Distance Decision
% Forest
%Parameters:
% model: a trained Helling... |
% setup basic environment for supercell
% input: sc_m, sc_n
% expect sc_m >=2 sc_n>=1
lattice_a=1.42*sqrt(3);
layer_d=[0,0,3.35];
% lattice_a*
a1=[sqrt(3)/2,-1/2]';
a2=[sqrt(3)/2,+1/2]';
sc_int_bottom_a1=[sc_n,sc_m];
sc_int_bottom_a2=[-sc_m,sc_n+sc_m];
sc_int_top_a1=[sc_m,sc_n];
sc_int_top_a2=[-sc_n,sc_n+sc... |
function Ahat= DICASimp(y) % dimension d, num trails
d=size(y,1);
phi = randn(d,1);
G1_phi = G1(phi,y);
G2_phi = G2(phi,y);
G3_phi = G3(phi,y);
M = G1_phi-G2_phi-2*G3_phi;
[U,D,~] = svd(M);
X = U*D.^(1/2);
psi1 = randn(d,1);
G1_psi1 = G1(X'\psi1,y);
G2_psi1 = G2(X'\psi1,y);
G3_psi1 = G3(X'\psi1,y);
M1 = G1_psi1-G2_p... |
clc
clear
%% Elements
n = 4; % number of elements in sde
m = 2; % number of other throwoff elements
l = 0; % number of other other elements
nfft = 4096*2;
T = 0.5e-6*nfft;
deltaT = T/nfft;
t = [0:nfft-1]/nfft;
time = t*T;
%% Input forcing function (run 'Phsforce.m')
disp('Loading Forcing function...')
Load = load('f120... |
function [ patches ] = getPatches( img, pSize, overflow )
%GETPATCHES Return a matrix where each column is a patche of img
% img is the image to be cut in patches
% pSize is the size of patches (they are squares)
% overflowSize is the number of pixels of 'overflow'
%
% Each patches is stored in one column the s... |
function out = distfcm(center, data)
out = zeros(size(center, 1), size(data, 1));
% fill the output matrix
if size(center, 2) > 1,
for k = 1:size(center, 1),
out(k, :) = sqrt( sum( ( ( data-ones(size(data, 1), 1)*center(k, :)).^2)' ) );
end
else % 1-D data
for k = 1:size(center, 1),
out(k, :) =... |
function vacc_core_init_xblock(varargin)
defaults = { ...
'veclen', 32, ...
'n_inputs', 1, ...
'arith_type', 0, ...
'bit_width_out', 32, ...
'bin_pt_out', 17, ...
'add_latency', 2, ...
'bram_latency', 2, ...
'mux_latency', 0, ...
'bin_pt_in', 0, ...
'use_dsp48', 1, ...
};
n_inp... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function samples = sampleFromHisto(histo, N)
% Samples from a non-parametric distribution modeled by a 3-D histogram
%
% Input parameters:
% - histo: input histogram to sample from. Can be of any arbitrary
% dimension
% - N: number of ... |
function z=int(z,N,h,x)
% Calcuiate the integral
sum=0;
for l=1:N+1
sum=sum+h*feval(@p,x(l))*z(l);
end
z=sum;
end |
function [L_class,aggClassEst] = ADABOOST_te(adaboost_model,te_func_handle,test_set,true_labels)
% global L;
% ADABOOST TESTING
%
% [L,hits] = ADABOOST_te(adaboost_model,te_func_handle,train_set,
% true_labels)
%
% 'te_func_handle' is a handle to the testing function of a
% ... |
function f_plot_export(hfig,SaveName)
FontSize = 10;
FontName = 'Arial';
% % FontName = 'MyriadPro-Regular';
%
% % figure dimensions in cm
% figure_width = 14;
% figure_height = 10;
% set(hfig, 'units', 'centimeters', 'pos', [5 5 figure_width figure_height])
%
% % setup axis plot properties
% % shading interp; % ... |
function [phi,zeta,eta] = TDD(Az,fs,fn,fnMin,fnMax,varargin)
% [phi,zeta,nu] = TDD(Az,fs,fn,fnMin,fnMax,varargin) estimates the mode
% shapes phi, modal displacements nu and modal damping ratios zeta of a
% structures using the time Domain Decomposition (TDD) mthod [1]
%
%% Inputs
% * Az: acceleration data. Mat... |
function call_price=american_call_futures_currcy_bin(S, K, r, r_f, sigma, time, no_steps)
%--------------------------------------------------------------------------
%
% DESCRIPTION:
%
% Pricing a futures currency option using a binomial approximation
%
%
% Reference:
%
% John Hull, "Options, Futures ... |
%Ridge regression object
classdef reg_ridge < handle
properties
beta
end
methods
%Carries out ridge regression and returns decision rule (beta)
%%%%%%%Arguments%%%%%
%obj=object
%resp_vec=response vector
%cov_matrix=covariate matrix
%alph... |
% System
A_true=[1 0.5 0.3]; B_true=[1 0.5];
% Data
x = randn(100,1); Pn = 0.01;
y = filter(B_true,[1 A_true],x)+sqrt(Pn)*randn(size(x));
% gamma-SVM parameters
epsilon = 0; gamma = 1e-1; C = 10; p = 5; mu = (.1:.1:1.9);
% Try different mu values
for i = 1:length(mu)
disp([num2str(i) ' de ' num2str(leng... |
u=0; a = 4; t = 10;
y = secondlaw4c(u,a,t);
|
clear paramsAll;
clear params;
params.Gridjob.runLocal = false;
params.Gridjob.requiremf = 3000;
params.Gridjob.wc_host = '';
params.Gridjob.jobname = 'JR_NoDriver';
params.Gridjob.continue = false;
params.Gridjob.initRandStreamWithJobid = true;
params.Gridjob.combParallel = false;
params.Gridjob.walltime = '00:59:00... |
% 3.5最后一问
function a=dtfs(x,n_init);
a=[];
w=2*pi/length(x); %fundamental frequency
for k=n_init:n_init+length(x)-1 %period from 0+n0 to N-1+n0
a_k=0;
for n=1:length(x)
a_k=a_k+x(n)*exp(-j*k*w*(n+n_init-1));
end
a=[a a_k/length(x)];
end
if n_init<... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function animate3DFigure(figHangle, increment, doSave, file)
% Visualize a 3-D figure by rotating along vertical axis
%
% Input parameters:
% - figHandle: handle to the 3-D plot to rotate
% - increment: Variation in angle from one frame ... |
function [structure] = AnalyseSwitchingIE(log, sdp)
%
% clear all; close all
% sdp = 3;
% fileID = fopen('LSw_IE6.txt');
% log = textscan(fileID,'%s %f %d %s');
% fclose(fileID);
% this function summaryses responses to the language switching task.
% It takes a single log, previously edited with coding for in... |
%% Create the random spectral points for the common channels
%% Set up the folders
uuidFolder = 'D:\Papers\Current\LARGIIDataCatalogInfo\uuidMaps';
saveFolder = 'D:\Papers\Current\LARGIIDataCatalogInfo\spectralRelationships';
baseFolders = {'O:\LARGDataCorrected', 'H:\LARGDataMaraCorrected', ...
'H:\LARGDataAsr_10... |
%% Features
O_dyn = 8*n; %# random gaussian directions for dynamics
O_w = 6*n; %# random gaussian directions for W
D_dyn = 2*O_dyn*n;
D_w = 2*O_w;
%exclude these components of x in f(x)
n_dyn = 1:2;
%exclude these components of x in B(x)
n_dyn_B = 1:6; %B should be constant for PVTOL
%exclude these components of x... |
function [receptor,Bou] = getGij_lay_psv_dwn(pota,receptor,Bou,...
Mpsv,M_sh,m,f,ops,mtrcs)
% obtner las tensores de Green entre segmentos:
% Bou.pt{i}.gG .gT
% y entre segmentos y receptores
% Bou.pt{i}.xG .xT
% en la frecuencia
% Allocate GreenFun variables
% now the ... |
%Computer Integrated Surgery, EN.600.445
%Alperen Degirmenci, Saumya Gurbani
%Copyright 2010 Johns Hopkins University.
function [a b samples] = readSampleReadings(filename, numA, numB)
%Reads the SampleReadings.txt and returns the corresponding G point3D structs
%and the number of frames
fid = fopen(filen... |
clear;
format long;
eff_pv=.15;
load('PV-RO-ERD data (365days) calculated in 07-Aug-2014.mat');
q_f0=q_f_max_ntr_erd;
q_p0=q_p_max_ntr_erd;
load('P_out fron PV.mat');
num_PV=20;
w_sun=num_PV*P_max*eff_pv*1e-3;%month 12
eff_erd=.98;
eff_hp=.9;
eff_ht=.9;
fos=73.45/100;%bar*kg/g
c_f0_ro=35;
c_b=0.1;
fai=0.5;
pi_f0... |
function albainit
% Initialize parameters for ALBA control in MATLAB
%
%==========================
% Accelerator Family Fields
%==========================
% FamilyName BPMx, HCM, etc
% CommonNames Shortcut name for each element
% DeviceList [Sector, Number]
% ElementList number... |
function [trunc_w,trunc_vec] = userdata_truncFFT(w,fft_w,center,half_width,skip)
% half_width = 4*half_width;
trunc_vec = fft_w(w < (center+half_width) & w > (center-half_width),:);
trunc_w = w(w < (center+half_width) & w > (center-half_width));
len = length(trunc_w);
trunc_vec = trunc_vec(1:... |
function plotActTermsOnMorphs2(cell_id,cell_layer,...
nrn_model_ver,nrn_pop_name,model_prefix,model_prefix2,varargin)
mat_dir = addPaths;
in.morph_alpha = 0.5;
in.morph_color = 'k';
in.term_act_col = 'r';
in.term_act_col2 = 'b';
in.term_lw = 1.5;
%in.term_lw = 7;
in.cell_inds_file = 'gen_figures/cellplot_inds_ls... |
% -------------------------------------------------------------------------------------------------------------------------
function net = add_adjust_layer(net, name, input, output, params, gain, bias, lr_gain, lr_bias)
% --------------------------------------------------------------------------------------------------... |
%1
im1 = imread("autumn.tif");
im2 = imread("football.jpg");
imshowpair(im1,im2,"montage");
%2
h = fspecial("gaussian",[5,5]);
%3
ycbcr = rgb2ycbcr(im1);
Y = ycbcr(:,:,1);
%4
ycbcr_copy = ycbcr;
Y_conv = imfilter(Y,h,"replicate");
ycbcr_copy(:,:,1) = Y_conv;
subplot(121); imshow(ycbcr2rgb(ycbcr)); title("original... |
function out = My_Imresize_BL(Input_Image, Resizing_Factor)
[rows, collumns, ~] = size(Input_Image);
out = zeros(rows*Resizing_Factor, collumns*Resizing_Factor);
for i = 1: size(out, 1)
for j = 1: size(out, 2)
x = i/Resizing_Factor - floor(i/Resizing_Factor);
y = j/Resizing_Facto... |
% Encode Data
%data(i)=1--> level chane
%data(i)=0--> no level change
function y=enc_data(x)
clf;
clear;
bits=8;
threshold=0.5;
data=rand(1,bits);
for i=1:length(data)
if data(i)>threshold
data2(i)=1;
else
data2(i)=0;
end
end
data
data2
figure(1)
subplot(3,1,1);
stairs(data2);
title('Original D... |
% generate_varian_stucture_20180208
% create by MP on 2/8/2018
%
% puts together the information from the data_list file to create the
% carbon and proton filepath names as well as the structure to save the
% data
%
% update(1) by MP on 2/19/2018
% improves list management
% load default values
if isempty(c13_seq_name... |
function logger = emptyLogger()
logger = struct('parameter',{},'iteration',{},'values',{},'PRAUC',{},'stdPRAUC',{},'dims',{});
end
|
clear all
close all
load('D:\abanobi\Documents\STAGE ISTERRE\gueguen\Archive\ERGATZ\CS2\060304_1326.002.mat')
vector = Z(:,2);
dt = 0.005;
sampling_period = dt;
sampling_freq = 1/sampling_period;
xt = 0:sampling_freq/(length(vector)):sampling_freq-sampling_freq/(length(vector));
Z_fen = zeros(12000,29);
Z_... |
% Uses PCA to get the best possible basis functions for the bi-exp filter
function [B_PCA] = PCA_basis(Sim_Struct, time_vec)
display('-I- Creating PCA basis matrix...');
%% Get relevant parameters from simulation struct
% Time parameters
% sec_inter = Sim_Struct.sec_interval(1);
% total_sim_time = ... |
% This MATLAB program checks the feasibility of LMIs from Theorems 1 and 2 of the paper
% A. Selivanov and E. Fridman, "Predictor-based networked control in the presence of uncertain time-varying delays," in 55th IEEE Conference on Decision and Control, 2016, pp. 501–506.
%% LMIs of Theorem 1
% System parameters
... |
%x = quadprog(H,f,A,b,Aeq,beq,lb,ub)
n=10;
e=ones(n,1);
mu=randn(n,1);
S=randn(n);
S=S*S';
r0=1;
[w,minvar]=quadprog(S,zeros(n,1),-mu',-r0,e',1,zeros(n,1),e); |
% Finite Difference Model of Geotherm + Surface Temperature Warming
% Jan 25 2016
clear all
figure(1)
clf
%% BOREHOLE DATA
load cape_thompson.dat;
data_depth=cape_thompson(:,1);
data_T=cape_thompson(:,2);
%% INITIALIZE
%Constants
k = 2.5; %W/mK
rho = 2000; %kg/m3
Cp = 2000; % J/kg K
kappa = k/(rho*Cp);
%Space Arr... |
function [glmModel] = designMatrixBlocks(selectedArray,glmnetOpt,glmModel)
basisFunction = normalize_var(normpdf(-1*glmnetOpt.bf.bfwidth:glmnetOpt.bf.bfwidth,0,glmnetOpt.bf.bfstd),0,1);
for i = 1:length(selectedArray)
currentCell = selectedArray{i};
%Defining features
touchDurMat = zeros(currentCell.... |
clc;clear;close all
a=0:0.01:90;
b = 2*(1-a/90)-tan((90-a)/2/180*pi);
plot(a,b,'LineWidth',1.8)
xlabel('\theta_s')
ylabel('\lambda_s')
set(gca,'fontsize',16);
grid on
axis([0 90 0 1])
set(gca,'xtick',0:10:90) |
n = 1/2;
while(n >= 1/512)
fp = (-3*e.^(0) + 4*e.^(0+n) - e.^(0+2*n))/(2*n);
display(fp);
n = n/4;
end
|
function [net,X,Xi,Ai,T,EW,Q,TS,err] = config(net,X,Xi,Ai,T,EW,configNetEnable)
% NNTRAINING.CONFIG
% Copyright 2010-2015 The MathWorks, Inc.
% Define default return values in case error is returned.
if nargin < 7, configNetEnable = true; end
Q = [];
TS = [];
% Input
% Missing inputs filled in with 0 column values
i... |
function q = DiscriminationTask(varargin)
% PSychophysics expeirment for UFlicker. The oberserver is presented with a
% fixation point. Then the background moves and at some variable time
% defined by objDelays the two patches appear on either side of the
% fixation point. THe task is to identify the highest contrast ... |
clear; clc;
%% Preset
Users = 200;
PacketLength = 1;
%% ALOHA simulation
Cursor = 1; %data cursor for arrays
for p = 0:0.0001:1 %arrival rate (per unit time)
G(Cursor) = Users * p; %average arrival rate (per unit time)
% Pure ALOHA
TimeSlot = 0.01;
PacketDuration = PacketLength / TimeS... |
function goodBoxesNonDups = detect_object( image_path, offset, slice,fidelity,car_model)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
addpath(genpath(('/home/ivashish/voc-dpm-master')));
im = imread(image_path);
%load('VOC2007/car_final.mat');
tt = tic;
goodBoxesNonDups = process(i... |
load data
new_cv = [2, 2; 3, 2];
D = [1, 2; 2, 1; 3, 1; 5, 5; 5, 6; 6, 5; 6, 6];
% C = [0.4, 0.7; 0.6, 0.3];
figure
scatter(D(1:end, 1), D(1:end, 2));
hold on
scatter(C(1:end, 1), C(1:end, 2));
axis([0 8 0 8])
grid on
n = 0;
while n < 10
new_cv = competitive_learning(D, new_cv, 0.4);
figur... |
function A=FUNfivePointLaplacian(n)
% This function constructs a five-point Laplacian matrix for an n x n
% mesh, with periodic boundary conditions
A=zeros(n^2,n^2);
for i=1:n^2
if(i>(n-1)*n), NORTH=i-(n-1)*n; else, NORTH=i+n; end
if(i<n+1), SOUTH=(n-1)*n+i; else, SOUTH=i-... |
function [score] = KL(map1,map2)
% map1: Saliency map
% map2: Fixation map
%make sure map1 and map2 sum to 1
if any(map1(:))
map1 = map1/sum(map1(:));
end
if any(map2(:))
map2 = map2/sum(map2(:));
end
% compute KL-divergence
score = sum(sum(map2 .* log(eps + map2./(map1+eps))));
end
|
function rv = bandstop(F, band)
%BANDSTOP: Remove frequencies in band from spectrum
% rv = BANDSTOP(F, band)
% - F : Fourier spectrum (one or more channels)
% - band: threshold frequencies (vector [low high])
[A, B] = size(band);
if(A~=1 && B~=2 && isinteger(band(1))~=1 && isinteger(band(2))~=1... |
%% stadio 2
function [Cin, W23, W24, W25] = stadio22(tau22)
% constants
Cox = CoxCapacity();
% channel lenght
L = 0.12*10^-6;
% load capacity for this stage
Cl22 = 100 * 10^-15;
% delay for this stage
% ratios
ratio23 = ratioMos('P', Cl22, tau22);
ratio22eq1 = ratioMos('N', Cl22, tau22);
ratio24 = ratio22eq1 *... |
function [naivetime,blockedtime,opt_blockedtime] = test(n,b)
A = randn(n);
B = randn(n);
tic, C = naive(A,B); naivetime = toc;
tic, D = blocked(A,B,b); blockedtime = toc;
tic, E = optimal_blocked(A,B,b); opt_blockedtime = toc;
assert(norm(C-D)/norm(C) < 1e-14);
assert(norm(C-E)/no... |
clc; clear; close all
data_dir = './';
fig_dir = './figs/';
fn_test = 't10k-images-idx3-ubyte';
fn_test_label = 't10k-labels-idx1-ubyte';
fn_train = 'train-images-idx3-ubyte';
fn_train_label = 'train-labels-idx1-ubyte';
%% read training images + labels
fid_train = fopen([data_dir, fn_train]); % images
[magic_train, ... |
function [orbs,orbitin] = findorbit(ring,varargin)
%FINDORBIT find the closed orbit
%
%Depending on the lattice, FINDORBIT will:
% - use findorbit6 if radiation is ON,
% - use findsyncorbit if radiation is OFF and ct is specified,
% - use findorbit4 otherwise
%
%[ORBIT,FIXEDPOINT]=FINDORBIT(RING,REFPTS)
%
% ORBIT: ... |
% Umbenennen eines Roboters in den Ergebnissen der Maßsynthese
% Wird benutzt, wenn in der Roboter-Datenbank ein Roboter umbenannt wird
% und die Ergebnisse mit der aktuellen Programmversion reproduziert werden
%
% Eingabe:
% OptName
% Name der Optimierung (z.B. 'ARK_3T2R_20220114_plfmorph')
% RobNameOld
% Vorheri... |
function medusaMuxInit(nodeid, muxaddr)
% function medusaMuxInit(nodeid, muxaddr)
%
% This is part of the Medusa software suite.
% Pascal Stang, Copyright 2006-2012, All rights reserved.
%
% $LICENSE$
global MEDUSA
global sock
% setup I/O port directions
data = [ hex2dec('40')+muxaddr 2 hex2dec('0006') ];... |
function [edv]=multinomial(Xtr, xltr, Xdv, xldv, epsilons)
edv = [];
wc=[];
wc0=[];
pred=[];
classes=unique(xltr);
N=rows(Xtr);
pri=[];
post=[];
for e=1:columns(epsilons)
for c=1:rows(classes)
i=find(xltr==classes(c));
NC=rows(i);
pri=[pri;NC/N];
xn=sum(Xtr(i,:));
xnd=sum(sum(Xtr(i,:)));
auxpost=xn/xnd;... |
% step piezo voltage and scan VNA;
% WTJ, 20180914
% WTJ, 20180922
% WTJ, 20190923
% For each detuning, take EOM dark, EOM, wide on-chip, narrow on-chip.
side = 'R';
V_bg = 2.7;
piezo_smoothset(V_bg);
pause(0.5)
Ps = getPs(instrs);
hsattenSet_fast;
%%
% Reset the VNA and scan.
% initZNB_wide_100Hz;
% zn... |
function argStruct = generateContinuousStochasticPolicyFcn(argStruct,numericSpec)
% GENERATECONTINUOUSSTOCHASTICPOLICYFCN generates continuous stochastic
% policy (use for PG, AC, etc. agents)
% Copyright 2019 The MathWorks, Inc.
% REVISIT: should this method live in sampling strategy?
outputstr = argStruct.Outp... |
function [ varargout ] = DrawBox( xlim,ylim,zlim, varargin )
%DRAWBOX Draws wire box specified by xlim, ylim, zlim
% xlim, ylim and zlim are a 2x1 array
% varargin goes directly to the plot3 function. Specify parent if
% necessary! Handy fact - if a 4th element for color is specified, it is
% the transparency o... |
% This is a class to wrap up a generic ChomboOutput class with specific MushyLayer
% functionality
classdef MushyLayerOutputOld < handle
properties
chomboOutput
mlComps
end
methods
function obj = MushyLayerOutputOld(dim, frame, output_dir, plot_prefix)
obj.mlComps =... |
clear all
close all
warning off
addpath('./functions');
addpath('./AgrawalICCV05MatlabCode');
EnvMap = 5; %%%Demo PARAMETER: Environment Value %%CHOOSE DIFFERNECE VALUES GHERE FOR DIFFERENT IMAGES FROM THE "../images" folder
interactive = 0; %DEMO PARAMETER Interactive Normals. Set this to "1"
NormalsUnif =... |
%%
figure,co=get(gca,'ColorOrder');
set(gcf,'DefaultAxesColorOrder',co([1 2 3 5 7 6 4],:));
plot(ldr_flat_slant_range.time,ldr_flat_slant_range.signals.values,...
ldr_ellipsoid_slant_range.time,ldr_ellipsoid_slant_range.signals.values),grid
cf=gcf;figs=cf.Number;
xlabel('Time, sec'),ylabel('meters')
fig_text='Sla... |
function p = hex_to_int16(h)
%HEX_TO_INT16 Convert hexadecimal string to int16 number.
%
% HEX_TO_INT16(H) converts the hexadecimal string H and returns the
% corresponding int16 numbers. Each row in H, representing one output value,
% must only contain characters in the set '0123456789abcdefABCDEF'.
%
% For e... |
% julia fractal
close all; figure;
load('0.julia.mat');
%mattread('0.julia.matt');
imshow(I);
F = getframe(gcf); [I, map] = rgb2ind(F.cdata, 256);
imwrite(I, map, 'julia.gif', 'gif', 'Loopcount', inf, 'DelayTime', 1);
for ii = 1:149
load([num2str(ii) '.julia.mat']);
%mattread([num2str(ii) '.julia.matt'])... |
clear; clc;
addpath Model Utilities
%% data set setting
dataset.name = 'GT_32x32';
dataset.tr_num = 8;
dataset.random = 0;
dataset.normalization = '255';
[train, test] = loadDataset(dataset);
%% Learning Dictionary from class-specific training data
params.num_Vi = 8;
params.num_G = 40;
params.maxIter = 20;
params.... |
function pa_genexp_avam_snd
% PA_GENEXP_SPATIALPRIOR
%
% This will generate an EXP-file of a spatial prior learning
% experiment. EXP-files are used for the psychophysical experiments at the
% Biophysics Department of the Donders Institute for Brain, Cognition and
% Behavior of the Radboud University Nijmegen, th... |
function fitpar_selected = select_fitpar(fitpar,keep_only)
% Build a structure, containing selected fitpar parameters
%
fitpar_selected=struct();
fitpar_selected.p = fitpar.p(keep_only);
fitpar_selected.sig =fitpar.sig(keep_only);
fitpar_selected.bp = fitpar.bp(keep_only);
fitpar_selected.bsig =fitpar.bsig(keep_only)... |
function run_svm_t(setting)
setpaths
data = load_data(setting);
result_dir = sprintf('result_%s', setting);
if ~exist(result_dir, 'dir')
mkdir(setting);
end
C = 1;
func = 'main_svm_t';
kernel_types = {'linear', 'poly'};
kernel_params = {0, 1.1:0.1:1.5};
N_set = [2 4 6 10 15 20];
for i = 1 : length(N_set)
N... |
%%read image
i = imread('~/Desktop/4.png');
j=rgb2gray(i);
%figure out the pad value to pad to white
if isinteger(j)
pad = intmax(class(j));
else
pad = 1; %white for floating point is 1.0
end
[r, c, ~] = size(j)
if r > c
newImage = imresize(j, 512 / r);
newImage(:, end+1 : 512, :) = pad;
elseif c > r
... |
function [pcaA V] = fastpca( A, k )
% 快速PCA
%
% 输入：A --- 样本矩阵，每行为一个样本
% k --- 降维至 k 维
%
% 输出：pcaA --- 降维后的 k 维样本特征向量组成的矩阵，每行一个样本，列数 k 为降维后的样本特征维数
% V --- 主成分向量
[r c] = size(A);
% 样本均值
meanVec = mean(A);
% 计算协方差矩阵的转置 covMatT
Z = (A-repmat(meanVec, r, 1));
covMatT = Z * Z';
% 计算 covMatT 的前 k 个本征值和本征向量
[V D]... |
function [ boolVec ] = detectAlternans( ACI,threshold )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
counter=0;
% threshold=0.2;
boolVec=zeros(length(ACI),1);
detect=7;
for i=3:length(ACI)
if(ACI(i-1)-ACI(i-2)>threshold && ACI(i)-ACI(i-1)< -threshold) || (ACI(i-1)-ACI(i-2)<-thres... |
function C = correlation_fun(corr,mesh1,mesh2,spthresh,matvec,x)
% CORRELATION_FUN returns the correlation matrix (or times a vector).
%
% C = correlation_fun(name,c0,c1,sigma,mesh1,mesh2,spthresh);
% C = correlation_fun(name,c0,c1,sigma,mesh1,mesh2,spthresh,matvec,x);
%
% Outputs:
% C: Either a sparse correlati... |
function varargout = set_reference_stateD(varargin)
[varargout{1:nargout}] = CoolPropMATLAB_wrap(328,varargin{:});
end
|
function y = sigmoid(x,t,a)
narginchk(1,3)
if nargin<3
a = 1;
else
assert(isscalar(a)==1,'a must be a scalar.')
end
if nargin<2
t = 1;
else
assert(isscalar(t)==1,'c must be a scalar.')
end
%% Perform mathematics:
y = 1./(1 + exp(-a.*(x*t)));
end
|
function plot_3DPose(points, nKeyPoints, edges, LiWi, colors )
scatter3(points(:,1), points(:,3),points(:,2), 400, 'k.', 'LineWidth',1)
hold on
% for pointid = 1:nKeyPoints
% if any(pointid == [5,6,7,13,14,15,16])
% label_ = [num2str(pointid),'L'];
% elseif any(pointid == [9,10,... |
function rb = FK_exp_7dof
%% manipulator twists
W1 = [0 0 1]'; W2 = [0 -1 0];
w1 = W1; q1 = [0;0;0.2025];
w2 = W2; q2 = [0;0;0.2025];
w3 = W1; q3 = [0;0;0.2025];
w4 = -W2; q4 = [0;0;0.2025+0.42];
w5 = W1; q5 = [0;0;0.2025+0.42];
w6 = W2; q6 = [0;0;0.2025+0.42+0.4];
w7 ... |
%% harmonyA.m
%
% genrate a 440Hz tone
Fs = 8000; % sampling rate
sep = power(2, 1/12);
A = 440; %tone A frequency
Cs= A*power(sep, 4); % tone C#
E = Cs*power(sep, 3); % tone E
t = (0:1/Fs:2); % from 0 to 2 second
% we reduce the amplitude by 0.2 to avoid distotion.
% add the three tones
y = 0.2*(sin(2*pi*(A... |
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