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function Space = ChebyshevSpace(Start,End,Length)
if (nargin < 3)
Length = 100;
elseif (nargin > 3)
error('Too many input arguments passed to LinearSpace')
end
switch (Start ~= End)
case (true)
Avg = (Start + End) / 2 ;
MidDist = (End - ... |
%------------------------------------------------------------------------%
%---Finite Differencing of Time Independent Schrodinger Equation---------%
%------------------for a particle in a box-------------------------------%
%------------------------------------------------------------------------%
clc
close all
clear... |
%%
% SUMMARY: Generates mxm synthetic image used as input for various
% experiments.
%
% Specifically, images are generated by first choosing a randomly positioned
% "foreground" square. The size of this square is a parameter
% ("fraction_fg") that is a fraction of the total image's area. Intensities
% of background p... |
tic;
videoReader = vision.VideoFileReader('store1.mp4', 'ImageColorSpace',...
'Intensity', 'VideoOutputDataType', 'uint8');
converter = vision.ImageDataTypeConverter;
opticalFlow = vision.OpticalFlow('ReferenceFrameDelay', 1);
opticalFlow.OutputValue = 'Horizontal and vertical components in complex form';
shapeIns... |
function C = main(X,epsilon,MinPts)
%% Run DBSCAN Clustering Algorithm
[IDX,noise,C]=DBSCAN(X,epsilon,MinPts);
%% Plot Results
PlotClusterinResult(X, IDX);
title(['DBSCAN Clustering (\epsilon = ' num2str(epsilon) ', MinPts = ' num2str(MinPts) ')']);
|
function z=ParticleAtTheLeft(NParticle,NStep)
%% Функция, возвращающая единичную реализацию зависимости n=n(t)
% NParticle-число частиц в левой половине ящика в момент времени t=0
% NStep-длина еденичной реализации
LeftN(1)=NParticle;
for i=2:NStep
Prob=LeftN(i-1)/NParticle;
if rand(1)<=Prob
Lef... |
% Spectral Ewald 0P (free-space) Laplace, basic accuracy/convergence computation
clear
rng(1);
N = 5000; % number of source particles
L = 3; % box side length
box = [L L L]; % periodic box
[x, f] = NEW_vector_system(N, box); % random sources
Neval = N; % number of evaluation points
% Ewald parameters
M0 = 16; % Set ... |
function Filter3 = gene_ThirdOctave_Filters(Fs)
%%%%%%%%%%%%%%%
%
% Filter3 = gene_ThirdOctave_Filters(Fs)
%
% FUNCTION
% This function designs IIR filters for each third octave bands with
% the following center frequencies
% Fc = [25, 31.5, 40, 50, 63, 80, 100, 125, 160, 200, 250, 315, 400, 500,... |
function R = rotMat(theta)
R=[cos(theta) -sin(theta); sin(theta) cos(theta)];
|
function diff_fig(old,new,var,i,j)
var_old=old.(var);
var_old=var_old(i,j);
var_new=new.(var);
var_new=var_new(i,j);
[ii,jj]=ndgrid(i,j);
subplot(1,3,1)
mesh(ii,jj,var_old)
title([var,' old'],'Interpreter','none')
subplot(1,3,2)
mesh(ii,jj,var_new)
title([var,' new'],'Interpreter','none')
subplot(1,3,3)
mesh(ii,jj,var_... |
w = linspace(-pi,pi);
b = [0.3 0.24];
a = [1 -0.9];
h = freqz(b, a, w);
subplot(2,1,1)
plot(w, abs(h))
title('mag(H(w))')
xlabel('w')
ylabel('mag (dB)')
axis([-pi pi 0 6])
subplot(2,1,2)
plot(w, angle(h))
title('phase(H(w))')
xlabel('w')
ylabel('phase (deg)')
axis([-pi pi -2 2])
|
function eig=QuickBisection(A,a,b,tol)
%%
% Using Sturm sequences and Bisection to solve for all eigenvalues of
% A in [a,b].
% This is a naive version which has no detection of bad edge cases.
% precondition: the eigenvalues of A must be unique in context of
% tolerence. A is tridiagonal and PS... |
function [L_j, L_jj] = Linear_Interp(t_j, t_jj)
%t_a = lower bound of integration
%t_b = upper bound of integration
%t_c =
syms tau
L_j = (tau - t_jj) / (t_j - t_jj);
L_jj = (tau - t_j) / (t_jj - t_j);
end
|
function m = mape(testY, pred)
% Compute mean absolute percent error
%
% m = mape(actual, pred)
%
% actual is a column vector of actual values
% pred is a matrix of predictions (one per column)
%
% m is the mean absolute percent error (ignoring NaNs) for each column of
% pred.
% Copyright 2014-2015 The MathWorks, Inc... |
%% ArimotoBlahutDiscretise usage example
% Iteration = 1000;
% Tollerance = 0.05;
%
% m = 1;
% n = 1000;
%
% sigma = 1;
% s = [1 2 3];
% createdata = @(s) normrnd(s, sigma, n, m);
% data = [createdata(s(1)), createdata(s(2)), createdata(s(3))];
%
% K = 0.6:0.01:1;
% binsnumbers = 10:1:50;
%
% [Cbias Clinear] = A... |
function indxout = BuildIndexMF(range,indxin)
% BuildIndexMF: Given a range, make the corresponding index
% See BuildRangeMF for more detail
% indxout = BuildIndexMF(range,indxin)
% If indxin is absent, the range is interpreted literally, otherwise the
% subrange of indxin is returned
for i = 1:size(range,2)
indxo... |
function this = plus(this, d2)
% See help on dbase/dbplus.
% -IRIS Macroeconomic Modeling Toolbox.
% -Copyright (c) 2007-2017 IRIS Solutions Team.
pp = inputParser( );
pp.addRequired('this', @isstruct);
pp.addRequired('d2', @isstruct);
pp.parse(this, d2);
%-------------------------------------------------... |
%% E.m
%
% Function that performs the matrix-vector multiplication that models a 2D
% parallel MRI experiment for given arbitrary k-space trajectory and
% sensitivity maps.
%
% INPUTS: * the original 2D image
% * a structure containing the parameters (k-space trajectory,
% sensitivity maps, metho... |
function [U, S] = pca(X)
%PCA Run principal component analysis on the dataset X
% [U, S, X] = pca(X) computes eigenvectors of the covariance matrix of X
% Returns the eigenvectors U, the eigenvalues (on diagonal) in S
%
% Useful values
[m, n] = size(X);
% You need to return the following variables correc... |
nboot = 1000;
genotype = 'WT';
epoch = 'sleep';
groupDefs = struct('genotype',genotype,'behavioral_state',{'sleeping','resting','moving'},'epoch',epoch);
groupNames = {'Sleeping','Resting','Moving'};
projDir = '~/Projects/rn_Schizophrenia_Project/';
baseFigDir = [projDir 'RZ-RW_PrelimAnalysisFigs/'];
baseFigDir = [bas... |
% newstring = stripString(oldstring, toremove)
%
% Removes all instances of string TOREMOVE from string OLDSTRING and
% returns the modified string.
%
% 05.18.07 - S.Fraundorf
% 11.21.09 - S.Fraundorf - replaced stripCharacter with this.
% improved efficiency with strrep
function newstring = s... |
%% SUMMARY_BAR -- Script interface to summary_bar()
conf = dsp2.config.load();
date = '072617';
kinds = { 'nanmedian' };
sfuncs = { @nanmean };
measures = { 'coherence' };
epochs = { 'reward', 'targacq' };
manipulations = { 'pro_v_anti' };
to_collapse = { {'trials', 'monkeys'} };
bands = Container( {[15, 30]; [35, ... |
function [ angle ] = anglecorrection( angle )
% ANGLECORRECTION removes the values that generate singularity on the
% measurement of the angles for all length of array
% for i = 2:length(angle)
% if ((angle(i) - angle(i-1)) < - 0.5 )
% angle(i) = angle(i-1) + (angle(i) - angle(i-1)) + pi * 2;
% elseif... |
function [ A ] = SudokuBacktracker( A )
[C,s,e] = candidates(A);
p=256;
k=sqrt(p);
while ~isempty(s) && isempty(e)
A(s) = C{s};
[C,s,e] = candidates(A);
end
if ~isempty(e)
return
end
%% backtracking
if any(A(:) == 0)
B = A;
z = find(A(:) == 0,1);
for x = [C{z}]
A = B;
... |
function [list, errors] = visitNode(tree, data)
errors = 0;
list = [];
len = length(data);
len_tree = length(tree);
for row = 1:len
x = data(row).line;
x_len = length(x);
x_new = zeros(1,70000);
y = x(1);
if x_len >1
for j = 2:x_len
... |
function [indicador]=compare(input_image,background,threshold)
indicador = 0;
%%
% Perform image difference from the new image and the background image
difference = (abs(input_image(:,:,1) - background(:,:,1)) > threshold) | (abs(input_image(:,:,2) - background(:,:,2)) > threshold) ...
| (abs(input... |
function J = costFunction(X, y, theta)
% X is the 'design matrix' contains our training examples
% y is the class labels
m = size(X, 1);
predictions = X * theta;
sqrErrors = (predictions - y) .^ 2;
J = 1 / (2*m) * sum(sqrErrors);
endfunction
|
% find which set of 4 segments has the top of the tee
% assume that the Tee bar is the longest side in one set that has 3 other
% shorter segments that total about the same length
% also reorder the set to give the crossbar 1st, the 2 sidebars second
% and the foot last
function [flag,headset] = findheadset(set1,set2)... |
function per_sol()
find_figure('per_sol'); clf; hold on;
h1=subplot(3,1,1); hold on;
h2=subplot(3,1,2); hold on;
h3=subplot(3,1,3); hold on;
R=5.0/2;
%%% calculate and plot the texture
% inf solition
xx0= -3*R:0.01:3*R;
a0 = 2*atan(exp(xx0));
plot(h1, xx0,a0, 'k-')
% periodic solitons
xx= -R... |
%% ranges
lb_x=-2;N_x=100;ub_x=2;
lb_y=-3;N_y=100;ub_y=3;
% lb_x=-5;step_x=0.2;ub_x=5;
% lb_y=-5;step_y=0.2;ub_y=5;
x=linspace(lb_x,ub_x,N_x);
y=linspace(lb_y,ub_y,N_y);
%%
xlab = 'weight w_1';
ylab = 'weight w_2';
% xlab = 'x';
% ylab = 'y';
%% Weighting for the sloped
[X,Y] = meshgrid(x,y);
Z = weighting(Y);
fig = fi... |
% simple accuracy track
function behavior_accuracy(vars)
wind = -49:50;
count = 0;
T_Range = 50:10:length(vars)-50;
accuracy = NaN(1,length(T_Range));
for i = T_Range
count = count+1;
Tr = i+wind;
accuracy(count) = mean((vars(Tr,3)-vars(Tr,6)>0) == (vars(Tr,9)==1));
end
figure;
plot(T_Range,accuracy*100);
y... |
function [ G ] = filtre_gradient( I,method )
switch method
case { 'sobel','prewitt' }
h = fspecial(method);
case 'roberts'
h = [-1 0 0;0 0 0 ; 0 0 1];
case 'MavoVassy'
h = [0 1 1 ;-1 0 1; -1 -1 0];
case 'laplacian'
alpha = input('laplacian... |
function postProb=GMM_LIKELIHOOD(d,DataPoint,K,PI,Means,Cov)
format long;
postProb=0;
for i=1:K
postProb=postProb+PI(1,i)*N(d,DataPoint,Means(i,:),Cov(:,:,i));
end |
%17-16
w = input("length of side of square in mm: ")/1000;
p = input("area density of material in kg/m^2: ");
massCir = (pi*w.^2*p);
massSqr = (w.^2*p);
Io = .5*massCir*w.^2 + massCir * w.^2 -(1/12)*massSqr*2*w.^2 - massSqr * w.^2;
sprintf("moment of inertia of plate is %.3f kg m^2", Io) |
function [y, opt] = WrapperPred(X, opt)
%
% WrapperPred(X, opt) gives the prediction for data in X using the fields
% in struct OPT.
%
% Use: For evaluating IterativeRLSWrapper functions.
%
% NOTE: This is function is probably obsolete and should be removed.
if ~isa(opt, 'GurlsOptions')
% warning('Compatibility mo... |
function fig = spikeWaveformsFromOps(ops, sp, varargin)
% PLOT WAVEFORMS
% Inputs:
% ops@struct - ops struct
% sp@struct - spikes struct
% Optional Arguments (as pairs)
% 'figure' - figure number or handle
% 'numWaveforms' - default 500
% 'postSpikeBuffer' - numbe of samples after spike t... |
% Calculate covariance according to spectrum
% spectrum S is p * p * fftlen dim matrix
% m is the max offset of covariance R you want
% note that the length of fft should at least 2*(m+1), bigger can reduce bias problem
function R = S2cov(S, m)
[p, q, fftlen] = size(S);
covs = real(ifft(S,fftlen,3));
R = zeros(p,p*(m... |
%% UiTerminating
classdef UiTerminating < event.EventData
properties
LeavePlantRunning logical;
end
methods
function this = UiTerminating(leavePlantRunning)
arguments
leavePlantRunning logical = false;
end
this.LeavePlantRu... |
classdef MvnJointGaussInfEng < JointGaussInfEng
% everything done in JointGaussInfEng
methods(Access = 'protected')
function [mu,Sigma,domain] = convertToMvn(eng,model,varargin) %#ok
mu = model.params.mu;
Sigma = model.params.Sigma;
d... |
%Monte Carlo De-noising for Binary Images
%Read noisy image data
rng(0);
format long
X = textread('stripes-noise.txt');
%Read true pixel values
I = textread('stripes.txt');
%Initialize parameters - *** UNCOMMENT the one you need ***
%WP = 0;
%WL = 0;
WP = 1;
WL = 1;
%WP = 1;
%WL = -1;
%WP = -1;
%WL = 1;
%WP = -1;
%WL... |
function direction_matrix=mtlrdir(filename,n_directions)
% function direction_matrix=mtlrdir(filename,n_directions)
[fid,message] = fopen(filename,'r','ieee-le');
if fid==-1 % file can't be opened
disp(message);
return;
end;
fseek(fid,512,'bof');
direction_matrix=fread(fid,2*n_directions,'f... |
clear
close all
clc
%Intervall
[X,Y] = meshgrid(-2.5:.25:2.5,-2.5:.25:2.5);
%Bestimmung des Tangentialvektors: 1 + f(x,y).^2
N = sqrt(1+Y.^2./X.^2);
U = 1./N;
%f(x,y)/N
V = -Y./X./N;
%Graph (0.5 = Verkürzungsfaktor der Vektoren)
quiver(X,Y,U,V,0.7) |
clear all
clc
%IVP condition
sx = [1 100];
x = linspace(5,10,sx(2));
Y = zeros(sx);
Y(1) = 2;
f = @(p,q) (sin(p))^3 + (tan(q))^(2);
for i = 1:sx(2)-1
Y(i+1) = Y(i) + f(x(i),Y(i))/sx(2);
end
plot(x,Y,'black');
axis equal; |
%% example of training and testing OSVR for expression intensity estimation
clear all; close all;
%% load data
% train_data_seq: an array of cells containing training feature sequences,
% each cell contains a D*T matrix where D is dimension of feature and T is
% the sequence length
% train_label_seq: an array o... |
function[W_WheelMainGear, W_WheelNoseGear, W_DynamNoseGear, LbsReqMainGear, LbsReqNoseGearStatic, LbsReqNoseGearDynamic] = WheelLoads(W0, x_NoseGear, x_MainGear, x_cg_min, x_cg_max, z_cg_max)
% This function is used to calculate the wheel loads
% Going off of the rough guidelines, we can decide to have the main gea... |
% Simple ndf_*.m example for CNBI loop. It implmements alpha rhythms
% monitoring on channel Cz, when coupled with a gTec gUSBamp.
% Classificiation output is forwarded to a feedback through iC interface.
function ndf_miw()
% Include any required toolboxes
ndf_include();
%addpath(genpath('/home/cnbiadmin/Git/Miw/MOD_... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% MXB324
% Group 1: Johnathan Adams, James Beattie, Georgia Harman, Thyraphol Sutanujinda
% Dalby Groundwater model
% Main Script Operations Script
%%%%%%%%... |
% Löschen
clc
close all
% überflüssig
clear all
% format long
% Fourier
syms x
fx = log(x+1);
%%
n1 = 3;
summe1 = 0;
for j=(-n1):n1
c = (1/(2*pi))*int(fx*exp( (-1i)*j*x), 0, 2*pi); % immer j statt n
summe1 = summe1 + c*exp(1i*j*x);
end
y1 = summe1;
% %%
%
% n2 = 9;
% summe2 = 0;... |
function response1 = getResponse1(gfunc,DNew,Vocc,occ,opt1D,index)
Nt = length(occ);
NsGrid = opt1D.NsGrid;
DIM = 1;
na = opt1D.Ne; % na = Ne;
response1 = zeros(NsGrid,1);
for i = 1:Nt
for j = 1:Nt
if( abs(occ(i) - occ(j)) > 1e-8 )
response1 = response1 + gfunc(Vocc(:,i)).*conj(Vocc(:,j))
... |
function [W, b] = My_FCNN (X, Y, learning_rate, activation_function, num_epoch, num_units, keep_prob, batch_size, update_algorithm, print_flag, plot_flag, save_flag)
%%%%%% My Fully Connected Neural Network
%%%%%% 函数功能描述：
% 输入训练数据X和对应标签Y以及其他网络参数，训练输出全连接神经网络各层神经元的权值矩阵W和偏置向量b（cell结构）
% 网络中的非线性激活函数采用ReLU或者... |
audio_file = strcat("Sample/","ADha.wav");
audio_file = char(audio_file)
[y,fs] = audioread(audio_file);
plot(psd(spectrum.periodogram,y,'Fs',fs,'NFFT',length(y))); |
function S = fSimulateRDMP(param, Stimulus)
% fSimulateRDMP models models a simple RDMP model for
%
% Inputs:
% Stimulus: structure of input
% Stimulus.prob probability of reward for a color
% param: structure of parameters value
% param.nSt... |
function [ Out_Im ] = bilinInterp( CFAIm,BinFilter,CFA )
%BILININTERP Summary of this function goes here
% Detailed explanation goes here
MaskMin=1/4*[1 2 1;2 4 2;1 2 1];
MaskMaj=1/4*[0 1 0;1 4 1;0 1 0];
if ~isempty(find(diff(CFA)==0)) || ~isempty(find(diff(CFA')==0))
MaskMaj=MaskMaj.*2;
end
Ma... |
function [norm_pdfs_bp] = txminer_apply_bp(data,norm_pdfs)
addpath BP_macos
% addpath BP
C = 0.01; beta = 1e-3; eps = 1e-2;
nComponents = length(norm_pdfs(1,1,:));
[nrows, ncols] = size(data);
% Get the data in the cell format required by SmoothBP
Beliefs = cell(nrows, ncols);
for i = 1:nrows
for j = 1:ncols
... |
function LONG_pushAVGtoICBMviaDARTEL(scans_to_process, templatepath)
%LONG_pushAVGtoICBMviaDARTEL - warp longitudinal images from subject avg to
%ICBM
%
% Syntax: scans_to_process = LONG_pushAVGtoICBMviaDARTEL( scans_to_process)
%
% Inputs: scans_to_process - array of objects of class LONG_participant,
% tem... |
function [p_y_given_x,y_pred] = h_o_layer(input,w,b,activation)
if activation == 'sigmoid'
p_y_given_x = (1 ./ (1 + exp(-(w*input+repmat(b,[1 size(input,2)])))));
elseif activation == 'softmax'
p_y_given_x = softmax((w*input+repmat(b,[1 size(input,2)])));
end
[pred_max y_pred] = ma... |
%% PCA降维
%% 加载数据
load fisheriris;
X = meas';
%% PCA降维
% 中心化
meanX = repmat(mean(X,2),1,size(X,2));
center_X = X - meanX;
% 求协方差矩阵
C = 1/size(X,2) * (center_X * center_X');
% 求特征值并降序排序
[W, Lambda] = eig(C);
sum(W.*W, 1) % 可以验证每个特征向量各元素的平方和均为1
feature = diag(Lambda)';
feature = feature(:,end:-1:1... |
function [best_err, A_out, Z_out, best_m] = Refine_EM(c,Z, y, Q, K) %round to K
N = length(y);
[c2, ind] = sort(c,'descend');
best_err = 1e300;
T=100;
m_upper = 8;
for m = 1:min(m_upper,length(c))
%count frequency of distinct patterns of length k
[Zuni,ia,ic] = unique(Z(:,ind(1:m)),'rows');
[ic2,ind2] = sort... |
function poly=inset(skel,h)
% INSET - Polygon inset from a straight skeleton
% Inset takes the vectorized skeleton, skel, of a polygon and uses that
% to compute the polygon inset of the original polygon. The inset
% distance is specified as h >= 0. The output polygon may contain a
% number of perimeters (w... |
function [ score ] = realizedRet( inSeq, varargin )
%% realizedRet 算从第N步到现在的收益
% [ score ] = realizedRet( inSeq )
% returns realized logarithmic return starting from N slices before.
%
% [ score ] = realizedRet( inSeq, MODE )
% MODE is optional. It decides if logarithmic or ordinary return will
% be used.
% 'c' log... |
%% Evaluate_EOS_Instruments.m
% RBES_Init_Params_EOS;
% [r,params] = RBES_Init_WithRules(params);
% mission_set{1} = create_test_mission('ACRIM',{'ACRIM'},1990,8,[]);
% mission_set{2} = create_test_mission('SOUNDERS',{'AIRS','AMSU-A','HSB'},1990,8,[]);
%
% orbit.altitude = 1300;
% orbit.i = 'near-polar';
% orbit.raan... |
function [minx, miny] = Refinement(impartL,impartR)
%% quadratic polynomial interpolation, *2-D*
% improved from
% Stereo Matching with Color-Weighted Correlation,
% Hierarchical Belief Propagation and Occlusion
% Handling, Qingxiong Yang
[a,b] = size(impartL);
ca = round(a/2); cb = round(b/2);
marg = round(ca/3); a2 ... |
function axes = principal_axes( M,d )
% returns first d principle axes in order as columns of matrix
S = cov(M);
axes = eigens(S);
axes = axes(:,1:d);
end
|
%% RUN EKF
% This script requires derive equations and the data from cameras
% measurements
% tic
clear
close all
T = 0.01; %(100 Hz) @frame rate=100fps; imu logged at 100Hz%
load('testData_Run.mat');
load('CamMatrix.mat');
c_FL=[stereoParams_Front.CameraParameters1.IntrinsicMatrix(3,1);stereoPa... |
%% legend_shark
% specification of a legend for shark
%
function legend = legend_shark
% created at 2016/09/05 by Bas Kooijman
%% Syntax
% legend = <legend_shark.m *legend_shark*>
%% Description
% Specifies a legend for shark
%
% Output
%
% * legend: (6,2) cell matrix with (marker, taxon)-pairs
% ... |
%% Raw FCV Tarheel data folders directory and subfolder paths
datadir = 'F:\EmilFristedMScDBMEW\Awake_data\RawData';
folderpaths = {'29\20130227_SAL',
'29\20130301_LY',
'32\20130227_LY',
'32\20130301_SAL',
'34\20130227_LY',
'34\20130301_SAL',
'52\20130911_SAL',
'52\20130913_LY',
'54\20140617_LY',
'54\20140619_SAL',
'5... |
rtpset='subset';
rtp_core;
|
function VisualizeWord (word)
% This function allows you to visualize the characters for a single word.
%
% Input:
% word: A struct array, each with an 'img' attribute that gives the 16x8
% pixel matrix for that image.
%
% Copyright (C) Daphne Koller, Stanford University, 2012
padding = zeros(size(word(1).img, 1),... |
function P = P(x,z)
% returns orth([x z]) described in the paper notation
% -------------------------------------------------------------------------
% x, z are matrices (n times r)
P = orth([x z]);
end |
z=1:7;
for i=1:7
z(i) = complex(randn,randn)
end
% am creat un vector cu elemente complexe
ma=media(z)
% ma imi calculeaza media aritmetica a partilor reale
g=patrat(z)
% functia g calculeaza patratul vectorului
p=transpusa(z)
% functia p returneaza matricea obtinuta prin inmultirea vectorului initial cu
%tr... |
function [ op,days ] = day2num(tt)
%day2num - convert Monday, Tuesday, etc to a series from 1-7
days = {'Monday';'Tuesday';'Wednesday';'Thursday';'Friday';'Saturday';'Sunday'};
op = zeros(size(tt));
for n = 1:7
fx = strcmpi(tt,days{n});
op(fx) = n;
end
end
|
%Kiran Rao
%ME 2016 - Section B
%902891012
%Homework 4: Problem 2
function HW4Pb2RaoKiran
deltaX = 2; %step size of x between each iteration
Y0 = 5; %lower boundary condition
Y20 = 8; %upper boundary condition
n = 9; %number of iterations
A = sparse(n,n); %create sparse(empty) mat... |
function [x, A, A_star,ThroatLoc,y] = getNozzle7(leng,Ed,Post_Length,Throat_Radius, endlength, divpm, minpt, taper, inlet)
% This nozzle has same expansion as getNozzle6 but a different inlet to
% allow for a more gradual taper
% Returns: x (position [m] along the nozzle)
% A (Area [m^2] along the nozzle... |
classdef SRGBToLinearGamma < LUT1DHalfDomain
%SRGBToLinearGamma Summary of this class goes here
% Detailed explanation goes here
methods
function value = getLUTValueForFloat(obj, floatVal, channel)
a = 0.055;
if floatVal <= 0.04045
value = floatVal / 12... |
function hsi = rgb2hsi(rgb)
% hsi = rgb2hsi(rgb)把一幅RGB图像转换为HSI图像，
% 输入图像是一个彩色像素的M×N×3的数组，
% 其中每一个彩色像素都在特定空间位置的彩色图像中对应红、绿、蓝三个分量。
% 假如所有的RGB分量是均衡的，那么HSI转换就是未定义的。
% 输入图像可能是double（取值范围是[0, 1]），uint8或 uint16。
%
% 输出HSI图像是double，
% 其中hsi(:, :, 1)是色度分量，它的范围是除以2*pi后的[0, 1]；
% hsi(:, :, 2)是饱和度分量，范围是[0, 1]；
% hsi(:, :, 3)是亮度分量，范... |
%生成未均衡化的清晰图像%
clear;
clc;
close all;
M=384;
N=288;
Fr=290;%Fr＝frame=第几帧
TH=35;
TL=20;
HL_num=100;
flag1=1;
flag2=1;
limit=5;%优化直方图算法级别
medfilt_grade=3;%中值滤波级别
ADC=14;%数据为14比特
fg=fopen('38CvData2000.dat','r');
WriterObj=VideoWriter('video_source.avi');% xxx.avi表示待合成的视频（不仅限于avi格式）的文件路径
writerObj.FrameRate = 25;
open(Wr... |
function [resultTableAll, resultTableAgg] = modelStatisticsAdaptation(modelFolders, functions, dimensions, instances, snapshots, exp_id, varargin)
% modelStatistics -- creates a table with statistics,
% each aggRow represents model and number of snapshot (combined),
% each colum... |
function [distToLineSeg] = distanceToLineSegment(startPt,endPt, pt )
L = sqrt((endPt(1) - startPt(1))^2 + (endPt(2) - startPt(2))^2);
global MMA_DEBUG;
global MMA_ABS_TOL;
global MMA_REL_TOL;
if (L < MMA_ABS_TOL)
distToLineSeg = sqrt((startPt(1) - pt(1))^2 + (startPt(2) - pt(2))^2);
return;
end
% else
lineTange... |
function drawPendulum(fh,x,theta,l,w,h)
% Draws pendulum on a cart
if nargin == 4
w = 0.15;
h = 0.10;
end
if not(isempty(fh))
figure(fh)
else
gcf;
end
clf, hold on, grid on
% draw cart
rectangle('Position',[x,0,w,h],'FaceColor','r')
% draw link
plot([x+w/2, x+w/2-l*sin(theta)], [h*0.9, h+l*cos(theta)], '-ok... |
function secondderivative
y = dsolve('D3y = 2*(D2y -1)*cotg(x)', 'y(pi/2) = 1, y')
end
|
function conn_subjects_loader()
% conn_subjects_loader
% Batch load all groups, subjects and sessions from a given directory root into CONN. This saves quite a lot of time.
% The script can then just show the CONN GUI and you do the rest, or automate and process everything and show you CONN GUI only when the results ar... |
%execute Q learning procedure
function [Q, rewards]=Q_learning(map, T, nStates, Q)
%get global settings
global mapSize;
global N_ACTIONS;
global initialQValue;
global pNoCarOnRowTest;
global showProgress;
global execLearning;
%generate distribution for Pno Car when learning
distrib=... |
function data=findKurtosis(data)
totalwindow=length(data);
for windowindex=1:totalwindow
tempwindow=data(windowindex);
data(windowindex).kurtosis=kurtosis(tempwindow.winSound);
end
end
|
clc; clear; close all;
load fourLetterWords.mat
% Cast every string to lowercase
dictionary = cellfun(@lower, fourLetterWords, 'UniformOutput', false);
initial_state = 'kalt';
goal_state = 'warm';
frontier_queue = Queue();
explored_set = {};
solution = 0;
tree = Tree(initial_state);
current_node = tree.root;
fr... |
function sFilesNotch = script_pre_sub8(SubjectNames, RawFiles, NoiseFiles, RawEventFiles, iSubj)
% Process: Create link to raw file
sFilesRun = bst_process('CallProcess', 'process_import_data_raw', [], [], ...
'subjectname', SubjectNames{iSubj}, ...
'datafile', {RawFiles{iSubj}, 'FIF'}, ...
'chann... |
function [x_ne, r_ne] = nels(A,b)
G = chol(A'*A);
y = linsolve(G',A'*b);
x_ne = linsolve(G,y);
r_ne = norm(A*x_ne-b);
end |
function h = findByTag(parentHandle, tag)
% FINDBYTAG
%
% Description:
% Convenience function for finding plot objects by tag
%
% Syntax:
% h = findByTag(parentHandle, tag)
%
% Input:
% parentHandle handle to figure or axes
% tag char
%
... |
function plotRangeSigi
clear all; close all;
format short e;
%
% Plot S_i vs T (at various strain rates)
%
fig1 = figure;
set(fig1, 'Position', [412 313 915 632]);
epdot = [1.0e-6 1.0e-4 1.0e-2 1.0e0 1.0e1 1.0e2 1.0e4 1.0e6];
color = [[1 0 0];[0 1 0];[0 0 1];[0.75 0.25 1.0];[0.25 0.7... |
function filenameSysParams=setSysParamsFilename(filenameParameters)
k=strfind(filenameParameters,'/');
if(isempty(k))
filenameSysParams='SysParams.mat';
else
k=k(length(k));
filenameSysParams=filenameParameters(1:k);
filenameSysParams=[filenameSysParams,'SysParams.mat'];
... |
% MODULUS 5IRMETHODp1et2
%
% DEPENDENCY
% 1CONSTANTS.mat
% 2cal_simdata.mat (for vsc)
% 3fpspec_simdata.mat
% FILE OUTPUT
% 5IRDB.mat
% clear variables;
% fprintf('5IRMETHODp1et2\nLOADING\n');
% load('.\mat\1CONSTANTS.mat');
% load('.\mat\2cal_simdata.mat');
% load('.\mat\3fpspec_simdata.mat');
% init
... |
function distance = computeDistanceMixDataWei(data, noCatFeatures)
%DO: catFeature distance will be 0 if there are a coincidence
%data: row wise is observation
%noCatFeatures; Number of cat feature
%OUT:
%distance: matrix, matrix(i, j) = distance( data(i), data(j))
% normalize the distance at every feature, i.e. ... |
% La classe DescriptorBuilder creare la variabile descriptor per
% per un'immagine.
classdef DescriptorBuilder < handle
properties
parameters ;
tmpBGR ;
tmpHSV ;
hsvConversionCache ;
random ;
end
... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% %%%
%%% Solve the Barotropic Potential Vorticity Equation %%%
%%% %%%
%%% d ... |
%Code for Question 1-3
clc;clear;
Re = 6378.145; %Earths Radius
rp = Re + 500; %Periapsis altitude
ra = Re + 800; %Apoapsis altitude
mu = 398600;
%Semi-Major Axis
a = (rp+ra)/2;
%Eccentrcity
e = (ra - rp)/(ra + rp);
%semi-latus rectum
p = a*(1-e^2);
%magnitude of the specific angular momentum
h ... |
function state = pooling(data,pooling_a)
% calculation layer operation
[data_row,data_col] = size(data);
[pooling_row,pooling_col] = size(pooling_a);
for m = 1:data_col/pooling_col
for n = 1:data_row/pooling_row
state(m,n) = sum(sum(data(2*m-1:2*m,2*n-1:2*n).*pooling_a));
... |
function display_table_values(data_matrix, cell_column, cell_row_label)
sTable = array2table(data_matrix,'RowNames',cell_row_label,'VariableNames',cell_column);
sTable
end |
mex waveResampleMex.cpp
addpath d:/users/jang/matlab/toolbox/audio
fileName='主人下馬客在船.wav';
[y, fs1, nbits]=wavReadInt(fileName);
fs2=9131;
% The following commands are synchronous if waveResample.m use the method of "linear" for interpolation.
z1 = waveResample(y, fs1, fs2);
z2 = waveResampleMex(y, fs1, fs2);
time=... |
symulacja=zeros(20398,4);
for hhy=1:20398
Xij(1,1)=Xij(1,1)-10;
mgr1;
symulacja(hhy,1)=hhy;
symulacja(hhy,2)=J1(1,4,2);
symulacja(hhy,3)=J1(2,4,2);
symulacja(hhy,4)=J1(3,4,2);
end
symulacja |
B = NET.G <= 0;
I = Iu;
[x,y,~] = find(B);
nbf = size(I,2);
%%
figure();
for i=1:nbf-1
a = I(:,i);
bf = reshape(a,[nx,ny]);
subplot (floor(nbf/3),3,i);
imagesc(bf); title(num2str(i)); axis off; hold on;
plot(y,x,'w.');
end
%%
% partition of unity
figure();
a = reshape(sum(I,2),[nx,ny]); surf(a); sh... |
% xSigmoidMapping.m
%
% Testing out the idea of taking measurements of R2' and DBV, and then mapping
% their ratio to values of OEF (probably using a sigmoid function). Script
% outline derived from Figure_R2pScatter.m
%
% MT Cherukara
% 16 April 2019
%
% Actively used as of 2019-04-16
%
% CHANGELOG:
%
% 2019-07-29 (MT... |
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