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function [] = fourierBarbara (inp_img)
[h w] = size(inp_img);
padded_img = zeros(2*size(inp_img));
padded_img((h/2)+1:(3*h/2) ,(w/2)+1:(3*w/2) ) = inp_img;
fim2 = fftshift(fft2(padded_img));
absfim2 = log(abs(fim2)+1);
figure; imagesc(absfim2, [-1 18]);
colormap(jet); colorbar;
%filter = ones(256,256)*0.6;
... |
% Compare refaced data with ground truth. Calculate L1 and L2 norm. Plot
% convergence fo training across epochs. Create summary images.
dataset = 5;
switch dataset
case 1
dirGroundTruth = fullfile('data','Dataset-blurred21-Guys-norm');
dirUnsup = fullfile('generate_images', '20181005-135815-blurr... |
function txyzCalibrated = calibrateAccelerometer(txyz, mode)
[accelerometerCalibrationData, ~] = loadCalibrationData();
% ellipsoid fitting disabled by default, because it does not seem to work that well
if ~exist('mode', 'var')
mode = 0;
end
if mode == 0
offset = acceleromete... |
function canoParam = FuncLearnStruct(U,V,L,lambda,quiet)
% Function to learn structure
%
% U: contNodeNum * sampSize, real/noisy continuous attributes data.
% V: discNodeNum * sampSize, real/noisy discrete attributes data.
% L: levels in each categorical variable
% Requires UGM at http://www.di.ens.fr/~mschm... |
%% Random Dot Motion Task
% TMS version
% Number of trials: nr_trial_per_cond 10 for 800 task trials
% (10 => 400 trials per function (*coh*dir*bins))
%now: 24 conditions -> nr_trial_per_cond=17 =>408 trials
%if error in disp a and b: make sure coherence is 0.3 not 3!
%% Constants
participant=input('p... |
function [psth_final,raster,t_ms,t_ms_r,NPSP,total_spikes,edges_ms,psth_check] = plot_psth(bin_fullname,start_ix_ms,sweep_duration_ms,extra_time_ms,channel_no,start_time_s,end_time_s,method,probe,t_bin_ms)
[spike_times_ms] = extract_spikes_pixels(bin_fullname,channel_no,start_time_s,end_time_s,method,probe);
t_bin_m... |
%% Assignment 2
%% Question 1(a)
% The Finite Difference Method is used to solve for electrostatic potential
% of a region, with $V=V_0$ on the left side and $V=0$ on the right side of
% the region. The top and bottom of the region are not fixed, so the
% problem is essential in one dimension.
close all
clear all
nx=... |
function hvcalibrate()
%
%
%hvcalibrate - issue 1.1 (17/05/2006)- HVLab HRV Toolbox
%-------------------------------------------------------
% Script to initialise the calibration graphic interface.
% "hvcalibrate()" display a window with channel parameters from
% the structure 'HV' if it already exists in t... |
function [] = plot_slopes_and_intercepts(data)
% The data input to this function is from e.g. FULLDATASET_PV.mat
session_inds = {};
session_inds{1} = 1;
session = 1;
for i = 2:size(data.orientation,1)
if data.orientation(i-1,:) == data.orientation(i,:)
session_inds{session} = [session_inds{session}, i];
e... |
global MPI_COMM_WORLD;
load 'MatMPI/MPI_COMM_WORLD.mat';
MPI_COMM_WORLD.rank = 103;
Alluxio_Row_mv_version3;
|
% pop_groupSIFT_convertToGroupAnatomicalRois()
%
% History: 12/09/2019 Makoto. selectDipWithLargerMoment() is supported.
% Copyright (C) 2016, Makoto Miyakoshi (mmiyakoshi@ucsd.edu) , SCCN,INC,UCSD
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the fo... |
% Première partie du TP, fonctionne uniquement avec IRIS
disp('*** Lecture de la base ***');
[filename, pathname] = uigetfile( ...
{'*.*', 'All Files (*.*)'; ...
}, ...
'open data'); S = [pathname filename];
sD=som_read_data(S);%lecture de la base
p=size(sD.data,2);%nb de colonnes dans la base (nombre... |
classdef Rect
%RECT Class for 2D rectangles
%
% A rectangle `[x,y,w,h]` is described by the following parameters:
%
% * Coordinates of the top-left corner. This is a default interpretation
% of `[x,y]` in OpenCV. Though, in your algorithms you may count `x` and
% `y` from the bottom-lef... |
%% convert_mach_mtx2struct.m
% convert our population arrays to population matrices in a struct to
% quickly calculate makespan.
% Matrices are m x n 0/1s (rows are machines, columns are jobs,
% corresponding to the initial sorted job array). m_ij = 1 if machine i is
% allocated to job j, and 0 otherwise. Each row sho... |
%% input
sphere_center = [0; 0;0];
sphere_radius = 0.55000000000000004;
line_point = [0.7309, 0.73099, 0.730988];
line_dir = [-0.00212813 , 0.00404455 , 0.00391235];
particle_position = [0.499979; 0.50004; 0.500039];
particle_vel = [-0.00212813; 0.00404455; 0.00391235];
particle_radius = 0.4;
contact_normal =... |
function [ output_args ] = kendrickClass(mz,cl)
%kendrickClass - visualisation plot
% Calculate the KMD
[nom,kmd] = kendrick(mz,[],'ch2');
% Now scatter through each type...
[unq,~,ind] = unique(cl);
numC = numel(unq);
cols = parula(numC);
ax = zeros(numC,1);
figure; hold on;
for n = 1:numC
fx = ind ... |
%BFGS method
x1=linspace(-2,2,100);
x2=linspace(-2,2,100);
[X1,X2]=meshgrid(x1,x2);
f = @(x1,x2)100*((x2-x1.^2)).^2+100*(1-x1).^2;
f(X1,X2);
Z=f(X1,X2);
contour(X1,X2,Z,0:10:500)
hold on
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
x=[0;0]; %starting point
tol=0.0001;
dx=0.01;
a=1.61803;
b=0.0005;
f = ... |
function LDOS = kmap(rs, d, V, npts, delta, dispersion)
% Calculates the LDOS map for set of scatters.
% inputs: rs = vector with the position of the scatters (in A)
% d = size of the map in A. (200A by default)
% V = bias voltage in V (0 by default)
% npts = number of pixels of the ma... |
function imgSeg = otsuBinarize(img)
x = 0:5:255;
[f,~] = ksdensity(img(:),x);
[num, loc] = findpeaks(f,x);
imgSeg = img;
imgSeg(imgSeg==0) = loc(1);
level = graythresh(imgSeg);
imgSeg = imbinarize(imgSeg,level);
end |
function y = diffCoef(x)
% y=ones(length(x),1);
% y=(x.^2+1)';
y=((x<.5)+10*(x>=.5))'; |
% Vowel synthesis using the Z-domain
%
% HY370 - Digital Signal Processing
% Laboratory Exercise #3
%
% Winter Semester 2016
%
% (c) G. Kafentzis, CSD, UoC, Greece
% Sampling frequency
fs =8000; % INSERT CODE HERE
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
%clear all
close all
filename='no_grad2';
nimpertr=50;
ntr=4;
TR=2;
noff=8-1;
dthr=30;
bim=2:7;
aim=9:11;
%[raw, lro, lpe, thk, total_tr, te, ti, ref_pos, ss, sli_val] = epirecon(filename);
expLength = 419;
stimLength = 10/2;
raw2avw(abs(raw), 'mag.img');
raw2avw(angle(raw)*1000, 'pha.img');
reg1 = ones(expLen... |
% Matt McDade
% System Simulation
% Midterm Exam Problem 4C
Nt=20;
Nr=17;
theta=linspace(0,2*pi,1001);
rho=linspace(0,1,1001);
tvec=linspace(0,2*pi,Nt);
rvec=linspace(0,1,Nr);
figure(1)
clf
hold on
plot(rho*0,4*rho-2,'k')
plot(4*rho-3,rho*0,'k')
hold off
for k=1:length(rvec)
z=rvec(k)*exp(i*theta);
... |
% This demo loads two grayscale images and efficiently computes the emd_hat
% between them in a similar to Peleg et al. paper: "A Unified Approach
% to the Change of Resolution: Space and Gray-Level".
% All computation here are done on dint32, which is a little more
% efficient than working on doubles.
% emd_hat is des... |
function data = ksmooth(ArrayData, r, sigma)
% smooths maps.
% Input: ArrayData = matrix to be smoothed
% r= radius of smoothing
% sigma = intensity of smoothing
% Outpot: data = smoothed version of data
if nargin==1, r=1; sigma=1; end;
if nargin==2, sigma=r; end;
[m, n]=size(ArrayData... |
function VMT_PlotShorelineFilled(Map)
% Plots a shoreline map given the shoreline data structure 'Map' (see
% VMT_LoadMap.m) on the current map
%
% Shoreline is is filled with channel cutout in this version.
%
% See Also: VMT_PlotShoreline
%
% P.R. Jackson, 12-9-08
brks = find(Map.UTMe == -9999);
for i =... |
clear;clc;
in = '../example_video/fil_cat.avi';
in_dat = double(readVideo(in));
thresh1 = 10;
thresh2 = -10;
sh_mode = 1;
filtMode = 2;
w = 0;
if filtMode == 1
lowFilt = [0 1/8 0; 1/8 1/2 1/8; 0 1/8 0];
elseif filtMode == 2
lowFilt = 1/16*[1 2 1; 1 2 1; 1 2 1];
elseif filtMode == 3
lowFilt = 1/9*[1 1 1... |
%pth = '/Users/wil/Documents/Work/Projects/Stratified-Wakes/dat/x/x/';
pth = '/home/jose/Desktop/Stability/dat/x/x/';
analysistype = 'spectrumdirect';
ISsaveplots = 1;
ISpatchloadmeshff = 0;
Stmax = 1.00;
shiftvecdirect = pi*linspace(0, Stmax, 11);
%shiftvecdirect(1) = pi*1.0e-3;
nevdirect = 5;
Lx = load('x... |
function [constrainedFoopsi, spikesReshaped, spikesMean] = plotStimResults(dF, constrainedFoopsi, stimParams, timeRadius, expName, expId, forceStackHeight)
% If there are more than 4 stimulation positions, might need more colors. But 4 should be enough.
if isempty(expName)
expName = '';
end
if isempty(expId)
expId =... |
function [bstat, k2stat] = subfnBootStrpv2(data)
% run once to find our how many values get bootstrapped
[ParameterToBS] = subfnProcessModelFit(data,0);
% find the size of the different variables
[Nmed, NParameters] = size(ParameterToBS.values);
N = length(data.Y);
NCov = size(data.COV,2);
% initialize the output valu... |
function [FspringsR, FspringsL] = calcGroundReactions(SpringPos, SpringVels,...
numSpringsBody, mu_s, mu_d, mu_v, Kval, Cval, ECR, ECL, latchvel,tscale,BeltSpeed)
% v3 implemented Fregly's springs
nframes = size(SpringPos,1);
Rhsprings = 1:numSpringsBody(1);
Rtsprings = numSpringsBody(1)+1:numSpringsBody(1)+numSp... |
function [W H] = nmf(V, w_size, num_of_iterations)
% random start values
W = rand(size(V,1),w_size);
H = rand(size(W,2),size(V,2));
% repmat magic utility
H_rep_index = reshape(repmat([1:size(H,1)],size(V,1),1),1,[]);
V_rep_index = reshape(repmat([1:size(V,2)],size(W,2),1),1,[]);
for i = 1:num_of_iter... |
function [N] = newtonBase(x, x_n)
%Berechnet das n-te Newtonbasispolynom
for j = (1:1:length(x))
N(j) = prod(x(j) - x_n(1 : end - 1));
end
end
|
function interpolateData(Tfreq,Duration,Variability)
%This function will interpolate or average to create data points in-line with the specifid frequency (Tfreq) in s
%It will add random variability to any interpolated data points
%If the resolution of optimization is faster than the stored data it will interpolate and... |
N=70; %the number of divisions
c=3*10^8; %speed of light
frequency= 2*10^9; %1 GHz
wavelength= 2*pi*c/frequency;
a=0.001; %radius
prompt = 'Length of Antenna in terms of lambda '; %request user input
len = input(prompt);
total_length=len*wavelength; %total length of the antenna
length=total_length/2; %length of one... |
val = normrnd(0,1, 20, 1);
%построение первого графического окна
subplot(1, 2, 1);
hist(val);
x = -3:0.1:3;
hold on;
plot(x, normpdf(x,0,1), 'LineWidth', 5);
subplot(1 ,2 ,1);
%построение второго графического окна
subplot(1, 2, 2);
plot(x, normcdf(x , 0, 1));
hold on
val = sort(val);
stairs(val, normcdf(val, 0, 1));
... |
function [b, eta, lambda] = mth_cart2oblsph_efit(e, xyz)
% MTH_CART2OBLSPH_EFIT comptues oblate spheroid coordinates given Cartesian
% coordinates and an ellipsoid eccentricity as the fit parameter.
%
%-----------------------------------------------------------------------
% Copyright 2017 Kurt Motekew
%
% This Source ... |
% Create Poisson process as described in RD17
nC = 10; % Total # of cells
T = 1200; % Total time (s)
lam = 0.1; % Avg firing rate for background process
fracVar = 0.1; % Fraction which is variable, vs. constant rate Poisson
S = makeAR(nC,T,lam);
S = fracVar*S + lam*(1-fracVar);
% E... |
close all
%Code to make a masked video based on ROI position
%Dependencies:
% Must run this code with Ca_Preprocess.m and Ca_1_ROI.m
File2 = strcat(Sample,VideoFileType);
InfoImage=imfinfo(File2);
mImage=InfoImage(1).Width;
nImage=InfoImage(1).Height;
NumberImages=length(InfoImage);
FinalImage=zeros(nImage,mI... |
function [c, ceq, X0] = test_optimality(ac, N)
[~,x] = fourierdiff(N);
t = ac.tf*x/(2*pi);
% [~,x] = chebdiff(N-1);
% t = 0.5*ac.tf*(1-x);
state = zeros(N,6); control = zeros(N,3);
for i = 1:N
sig = get_traj(t(i), ac.tf, ac.coeffs, ac.N);
state(i,4:6) = [sig(1), sig(2), sig(3)];
... |
function res = GetCandidatesFromRecState( RecState )
%GETCANDIDATESFROMRECSTATE Summary of this function goes here
% Detailed explanation goes here
res = '';
segmentationPoints = [RecState.SegmentationPoints];
for i=1:length(segmentationPoints)
if (i==1)
startIndex = num2str(1);
else
... |
function swcCallback(obj,figH,eventData)
%% read swc file
obj.dendReadSWC();
%% detect branches
obj.dendAddBranches();
%% recalculate mask
obj.dendMaskUpdate(); |
function writeStatsToFileClusterFirstV2( dataStructCategory, dataStructNumeric, fl, saveFilePath, save_file)
%save_file: include path and folder
%data to write to html format
imgFolder = 'Figures/';
fid = fopen([saveFilePath, save_file], 'w');
fprintf ( fid, '<html>\n');%html tag
fprintf ( fid, '<head> ... |
function Kj=reinforce(t,y)
R=8;
L=6e-5;
J=0.02;
Kt=1;
Kb=1;
Tl=1;
N=1;
phi=0.0015;
A=[-R (-Kt);(Kt) 0];
B=[1;0];
T=20;
l=2;
P=rand(2,2,T);
Q=[1 0;0 1];
r=1;
Kj=eye(1,2);
P1=eye(2,2);
for i=2:1:T
P(:,:,1)=P1;
P(:,:,i)=transpose(A-B*Kj)*P(:,:,i-1)*(A-B*Kj)+Q+transpose(Kj)*r*Kj;
end
Kj=pinv(r+transpose(B)*P(:,:,T)... |
function [edge_list, nedges] = eid2adj_edges_usestruct(eid,edges,v2hv,sibhvs,usestruct)
[edge_list, nedges] = eid2adj_edges(eid,edges,v2hv,sibhvs,usestruct); |
function [s,ernst] = ernst_eq(tr,t1,flip)
% function [s,ernst] = ernst_eq(tr,t1,flip)
flip = flip/180*pi;
E1 = exp(-tr./t1);
s = (1-E1).*sin(flip) ./ (1-cos(flip).*E1);
ernst = acos(E1)/pi*180;
return |
% top row initial positions and the bottom is velocities of sol0
tspan = [0, 20*pi];
m = [1, 100];
sol0 = [1; 0; 0; 0; 0; 0;
0; 10; 0; 0; 0; 0];
figure(1)
[t,sol] = ode45(@(t,y) nbody(t,y,m), tspan, sol0);
plot3(sol(:,1),sol(:,2), sol(:,3), 'm-');
title('ode45')
figure(2)
[t,sol] = ode23(@(t,y) nbody(t,y,m), ... |
function measures=evaluateResult(Labels,PredictedLabels, batchSize,MethodName)
n=size(Labels,1);
T=ceil(n/batchSize);
measures.precision=zeros(T-1,1);
measures.recall=zeros(T-1,1);
measures.accuracy=zeros(T-1,1);
measures.F1=zeros(T-1,1);
totalNumber=0;
trueNumber=0;
alpha=0.95;
for t=1:T-1
index=(t)*batchSi... |
% Distribution code Version 1.0 -- Oct 12, 2013 by Cewu Lu
%
% The Code can be used to evaluate your detection results in our Avenue Dataset, build based on
% [1] "Abnormal Event Detection at 150 FPS in Matlab" , Cewu Lu, Jianping Shi, Jiaya Jia,
% International Conference on Computer Vision, (ICCV), 2013
%... |
function [Sig] = CMR_randMod_3AFC(noise_bands,target_f,SNRdB,n_mod_cuts,target_modf,fs,tlen,coh,bp_mod_fo)
t = 0:1/fs:tlen-1/fs;
if size(noise_bands,1) ~=3
error('Currently expect 3 noise bands')
end
bp_filt_mod = fir1(bp_mod_fo, [n_mod_cuts(1) n_mod_cuts(2)]*2/fs,'bandpass');
bp_fo = round(1/(min(min(noise_ban... |
% HW 5 problem 1
% Steven Macenski last edited Oct 2, 2013
a = [4 -1 0 3;-2 3 1 -5;1 1 -1 2; 3 2 -4 0];
b = [10;-3;2;4];
x = a\b;
fprintf('The solutions for variables are as follows:\n %f\n %f\n %f\n %f\n',x); |
function out = main()
switch getenv('ENV')
case 'IUHPC'
disp('loading paths (HPC)')
addpath(genpath('/N/u/hayashis/BigRed2/git/vistasoft'))
case 'VM'
disp('loading paths (VM)')
addpath(genpath('/usr/local/vistasoft'))
end
icvf = niftiRead(fullfile(pwd,'NODDI','AMICO','NODDI','FIT_ICVF.nii.gz'));
od = niftiRea... |
function H = hilmat(n)
%
% function H = hilmat(n)
%
% Hilbert matrix
%
% Input -
% n: order of Hilbert matrix
%
% Output -
% H: n-order Hilbert matrix
%% Parameter check
if nargin ~= 1
error('Error! Number of inputed parameter shoule be equal to 1.')
end
if numel(n)~=1 || ~ismatrix(n)
error('Error! Inputed p... |
%% init_gearbox.m
global h; |
function y=nextA(A,x)
end |
% 保存特征到文件夹的版本
% 选择不同层的特征+PCA+进行liblinear实验
%
clc
clear
net1 = dagnn.DagNN.loadobj(load('D:\myself\matlab\matlab_documents\dynamic_image\exp\ntu\net-deployed.mat')) ;
net1.mode = 'test' ;
imdb = load('D:\myself\matlab\matlab_documents\dynamic_image\exp\ntu\imdb.mat') ;
% imdb = imdb.imdb;
b = 1;
opts.dataDir = fullf... |
% load('resultWorkspace500.mat');
gen = pop(1,:);
% close all;
% figure;
% img = drawGAImage(gen, imageSizeX, imageSizeY, circlesNum);
% imshow(img)
% compare images
figure(20);
subplot(1,3,1);
original = imread('fotoCustom.jpg');
% imageSizeY= 200;
% imageSizeX = 200;
original = imresize(original, [imageSizeY image... |
function [ fullpaths ] = get_paths( default_folder )
%get_paths Ask the user for the folder containing iamges to analyse
folder_name=uigetdir(default_folder,'Choose a folder to process'); % UI prompt
if folder_name==0
msg='No folder selected, I quit';
error(msg);
return;
end
y=dir(folder_name);
%need to ... |
function z = circular_conv(x, y)
%debug
% x = [5 1 -2 4];
% y = [1 2 3];
%end debug
if (length(x)>length(y))
N = length(x); % zero padding to length N
else
N = length(y);
end
xpad = [x zeros(1,N-length(x))];
ypad = [y zeros(1,N-length(y))];
z = zeros(1, N);
for k=0:(N-1)
fo... |
function phalgdt(varargin);
% phalgdt( [...] );
% Gas Deck T
h = timeplot({'Air_T','Gas1T','Gas2T','Gas3T','Gas4T','Gas5T'}, ...
'Gas Deck T', ...
'T', ...
{'Air\_T','1','2','3','4','5'}, ...
varargin{:} );
|
function W = STL_MLR(Xtrn, Ytrn, param,opts)
no_trn_idx = [];
for i = 1: length(Xtrn);
if size(Ytrn{i},1) >=1
W(:,i) = regress(Ytrn{i},Xtrn{i});
% W(:,i) = lasso(Xtrn{i},Ytrn{i},'lambda',param);
else
no_trn_idx = [no_trn_idx,i];
end
end
tmp = setdiff(1:length(Xtrn... |
%% V2 FLD classifier with posterior
% variance normalization
vnorm = @(x) bsxfun(@rdivide,x,std(x));
% get keys with V1-V2 recordings
keys = fetch(StatArea.*StatsSites('exp_date>"2013-08-05"'));
% intialize variables
[ad, dv, ed, rd, mn, ps,cpV2] = initialize('cell',length(keys),1);
parfor ikey = 1:length(keys);d... |
function this = power(a, b)
% times Overloaded power and mpower for sydney class.
%
% Backend IRIS function.
% No help provided.
% -IRIS Macroeconomic Modeling Toolbox.
% -Copyright (c) 2007-2017 IRIS Solutions Team.
persistent SYDNEY;
if isnumeric(SYDNEY)
SYDNEY = sydney( );
end
%-----------------------------... |
function [fx] = fi(in)
% x = in(1); y = in(2);
% fx = 100*(y-x^2)^2+(1-x)^2;
% fx = in(1)^2+in(2)^2+in(1)*in(2)+in(1)*in(3)+in(3)^2;
% Beale's function:
% y = in(2);
% x = in(1);
% fx = (1.5-x+x*y)^2+(2.25-x+x*y^2)^2+(2.625-x+x*y^3)^2;
%Rosenbrock
fx = 0;
for i = 1:3
fx = fx + 100*(in(i+1)-in(i)^2)^2 +... |
function [] = parseTiles(scanFile, regions, wavelengths, varargin)
p = inputParser;
p.addRequired('scanFile', '', @ischar);
p.addRequired('regions');
p.addRequired('wavelengths', @(x)validateattributes(x,{'numeric'}));
p.addParameter('inDir', '', @ischar);
p.addParameter('outDir', '', @isc... |
function [vx, vy, vz] = mm2vox( hdr, mxyz )
%function [vx, vy, vz] = mm2vox( hdr, [mx,my,mx])
%
% convert from mm to voxels using the AVW
% header information (including the origin)
% in AVW the origin is in voxels
%
% (c) 2005 Luis Hernandez-Garcia
% University of Michigan
% report bugs to: hernan@umich.edu
%
%
mx =... |
% cellDists.m
% finds distance between outline and cell center at each outline pixel
% Inputs:
% r = row locations of outline
% c = column locations of outline
% cent = center of cell
%
% Outputs:
% dists = vector of euclidean distances
%
% Written by Carolyn Pehlke
% Laboratory for Optical and Computational Instrument... |
b=2;
c=1;
i=1;
A=[0 0 1 0 0; 0 b c 0 0; 1 c 0 c 1; 0 0 c b 0; 0 0 1 0 0];
for L=-2:0.001:2
[r,t]=comput(5,A,L);
R(i)=r;
T(i)=t;
i=i+1
end
L=linspace(-2,2,4001);
subplot(3,2,1)
plot(L,Real,'.');
xlabel('eigenvalue')
ylabel('real(Det(M))')
subplot(3,2,2)
plot(L,Imag,'.');
xlabel('eigenvalue')
... |
%{
Copyright (c) 2017 Raghvendra V. Cowlagi. All rights reserved.
Copyright notice:
=================
No part of this work may be reproduced without the written permission of
the copyright holder, except for non-profit and educational purposes under
the provisions of Title 17, USC Section 107 of the United States Cop... |
%% This script contains a mouving boundary diffusion problem using an analytical solution
clear variables;
%% INPUT
C_0 = 0.3; %initial concentration
C_1 = 0.7; %boundary concentration
t = 60000*60*60; %time in s
dx = 1; %spatial resolution in um
l = 1000; %profile length in um
D = 1E-4; %diffusion coeffi... |
function [TR, TT,p_idx,q_idx, ER, t] = corres_pfh(q,p,varargin)
% Perform the Iterative Closest Point algorithm on three dimensional point
% clouds.
%
% [TR, TT] = icp(q,p) returns the rotation matrix TR and translation
% vector TT that minimizes the distances from (TR * p + TT) to q.
% p is a 3xm matrix and q ... |
function [ bestSAD_R, bestSSD_R, w , h ] = Dhuliya_Arjun_Wiki_TM( I,T )
% implementing template matching calculating the SAD,
% Wikipedia was refered for the algorithm
% https://en.wikipedia.org/wiki/Template_matching
% I is search image and T is template image
I = im2double(I);
%resize image if too big, save tim... |
function [y, echoPix] = getMeanROI(handles, mask)
%GETMEANROI Beregner middelintensiteten af en ROI.
%
% INPUT:
% handles: handle til elementer i gui
% mask: maske for den ROI, som middelintensiteterne skal findes for
%
% OUTPUT:
% y: Middelværdierne for ROIen
% echoPix:
% - echoPix.Pixels: hv... |
function potentialOffspring = Random_Init_M400(angles_num)
% $Rev: 690 $
% $Author: maxim $
% $Date: 2014-10-28 07:25:19 +0400 (Tue, 28 Oct 2014) $
potentialOffspring = [];
num_sec_str=fix(angles_num/7);
k = randi([1,num_sec_str],1,1);
l=zeros(1,k);
for i=1:(size(l,2)-1)
%r=randint(1,1,[1,fix(angles_num/k/2.5)])... |
% set up an array for the photons,
% x, y, z, mu_x, mu_y, mu_z, weight, received
% 0, 0, 0, 0 , 0 , 1 , 1 , 1 - initial values
% 1, 2, 3, 4 , 5 , 6 , 7 , 8 - Position
% photon(:,1) == X POSITION
% photon(:,2) == Y POSITION
% photon(:,3) == Z POSITION
% photon(:,4) == ux
% photon(:,5) == uy
% pho... |
function [dict, desc] = getFF49Classification()
% DO NOT EDIT THIS TEXT
%
% 1 Agric Agriculture
% 0100-0199 Agric production - crops
% 0200-0299 Agric production - livestock
% 0700-0799 Agricultural services
% 0910-0919 Commercial fishing
% 2048-2048 Prepared feeds fo... |
clear all;
close all;
clc;
TarPath = 'D:\文件夹1\';
[TarFileName,TarFileNum] = TargetFile(TarPath);
SrcPath = 'D:\文件夹2\';
[SrcFileName,SrcFileNum] = SourceFile(SrcPath);
destination = 'D:\结果';
FileExtraction(TarPath,TarFileName,TarFileNum,SrcFileName,SrcFileNum,destination); |
astronaut = load_image('Astronaut.tif');
N = 1024;
[spectrum, ~] = complex_image(astronaut, [N N]);
imagesc(mag2db(spectrum));
saveas(gcf, "output/impl3_spectrum.png")
close(gcf)
% generate notch filter
mask = ones([N N]);
mask(:,476:485) = 0;
mask(:,542:549) = 0;
% generate band-... |
lambdaS = 0.1;
medFilterWL = 400; % length of the maj/med filters' windows (400 = 2s)
majFilterWL = 2000; % don't forget to change this in the code...
threshold = 6/nModules * majFilterWL; % empirically determined
tic;
fftTorques2('s',1,0.9,lambdaS,[1 2]); % figure 2 / 27650
fftTorques2('u',2,0.9,lambdaS,[3 4]); % ... |
%Oppgave 2b
nCell={};
for n=1:4;
x=input(['Input string with a length of ' num2str(n) ' elements: '],'s');
if length(x)==n & isstrprop(x,'alpha')
nCell(end+1)=cellstr(x);
else if ~isstrprop(x,'alpha')
error('Not a string. Try again');
else
while length(x)~=n
... |
function [rho_avg_c, C_c]=fn_get_cores_rho_C(X_le, r_ic, T_of_r, R_c, P_c, EOS_generator)
C_c = nan(length(X_le), length(r_ic));
rho_avg_c = nan(length(X_le), length(r_ic));
[EOS_params_l, EOS_l, EOS_params_s, EOS_s] = EOS_generator(X_le);
for i=1:length(X_le)
for j=1:length(r_ic)
... |
function [] = Image_Rotation(n,A)
Resultant=[];
if n==length(A)
for i=1:length(A)
%disp(i)
for j=1:length(A)
%disp(j)
x=(n+1)-j;
Resultant(i,j)=A(x,i);
end
end
end
disp(Resultant)
end
|
T = 300.0;
edot = [0.001 0.002 0.02 0.085 1.1 8.5 30 1000];
load AlSigEpsEleiche0001s300F.dat
a01 = AlSigEpsEleiche0001s300F;
load AlSigEpsEleiche0002s300F.dat
a02 = AlSigEpsEleiche0002s300F;
load AlSigEpsEleiche002s300F.dat
a03 = AlSigEpsEleiche002s300F;
load AlSigEpsEleiche0085s300F.dat
a04 = AlS... |
load MFCCExpTest
women=MFCC{4};
clear MFCC;
load MFFCTrainingSampled
output =DynamicTimeWarp(women(313:end),MFCC); |
function [ J ] = Compute_loss( X_input, Ys_batch, convnet )
% [n_lend, N] = size(X_batch);
% [n_len, ~] = size(Ys_batch);
% d = n_lend / n_len;
%
% loss = 0;
% for i = 1:N
% X = reshape(X_batch, [n_len, d]);
% X_batch1 = max(MFs{1} * X, 0);
% X_batch2 = max(MFs{2} * X_batch1, 0);
% S = W * ... |
clear;
voltage_points_313 = 0:0.01:1.8; %course for the entire voltage range, 10u
voltage_points_324 = 0.8:0.001:1.0;%10u
voltage_points_fine = 0:0.001:1.8;
micro = 0.000001; %mu = 1e-6
pico = micro*micro;
%normalised = extract_td_data("H:\FYP\Sigmoid stuff\sigmoidal_time_domain_output3.csv");
x_313 = extract_td_... |
function r = tsrms(music0)
[data,fs] = audioread(music0);
md = mono(data);
% 秒
t = 1;
%最後の方のデータは切り捨て
l = fix(length(md)/(44100*t));
r = zeros(1,l)';
for i = 1:l
r(i) = rms(md((i-1)*44100 + 1:i*44100));
end |
function [ snpo, err, errmsg ] = snpmodifydc( snpi, dcmat, fresol )
%% spinsertdc: modify existing DC point in S-parameter struct.
% If snpi does not contain a DC point, an error will be returned
%
% input variables:
% snpi (struct): SNP struct containing S-parameter without DC point.
% dcmat ... |
% FIFO
% The script devises the simple FIFO schedule for v2x communication
% Size of the packets in bits
size = 8*[1300, 180, 180, 140, 140];
% Capacity of the channel in kbps
C = 20000:5000:120000;
% Number of objects created by the sensors per second
num_of_objs = [10,10,10,10,10];
% Total number of objects to be s... |
function [residual, g1, g2, g3] = NK_GLSV07_iclm_rep_dynamic(y, x, params, steady_state, it_)
%
% Status : Computes dynamic model for Dynare
%
% Inputs :
% y [#dynamic variables by 1] double vector of endogenous variables in the order stored
% in M_.lead_lag_... |
%Mx =x has units cSt - centistoke - multiply by fluid density for visc
% '1836' : deltattimelaps=120
% '1837' : deltattimelaps=48
% '1847' : deltattimelaps=150
% '1856' : deltattimelaps=120
% '1857' : deltattimelaps=180
clear
close all
nu=0.5;
CurrentDir=pwd();
%visc = Pa.s
%delta_gamma = ... |
function DoChanFunctions(action,h)
if (nargin == 1)
h = gcbf;
end
switch(action)
case 'SetCAxProp'
set(h,'KeyPressFcn','DoChanFunctions KeyTrap'); %This seems to get overwritten
haxc = getappdata(h,'haxc');
axcol = [0.6 0.6 0.6];
set(haxc,'Tag','ClustAxes', ...
'Box','off',...
'XColor',axcol,'YColor',axcol,..... |
% --- Loads the rp2, rv8, and pa5s
function [RP2,RV8,PA5x1,PA5x2] = load_circuits_gap()
% Connects to RP2, RV8, PA5s, loads and runs RV8 circuit
% Checks whether the circuits were loaded properly
path='C:\Users\user\Documents\Jeff\';
%rp2circ='tdt circuits\RP2_Mixer.rco';
rv8circ='speaker sw... |
% CLASSPERF Classification performance.
% OUT = CLASSPERF(LPRED,LTRUE) measures distinct classification
% performance indices, where LPRED are the predicted labels by the
% classifier and LTRUE are the actual labels. OUT is a structure
% containing the following indices: Matthews correlation coefficient (MCC),
... |
%--------------------------------------------------------------------------
%% Deep Learning Basics : adjustInputImageSize
%--------------------------------------------------------------------------
%
% This function adjusts the size of the image as required by the input
% layer of the CNN
%
% [in] : imgPath (image pa... |
function [AUC, RT] = fnEP_SPAM_L2(X_train, Y_train, X_test, Y_test, options, optL2)
% SPAM_L2: Stochastic Proximal AUC Maximization with L2 penalty term
%--------------------------------------------------------------------------
% Input:
% X_train: the training instances
% Y_train: the vector of lab... |
function assert_cell_with_strings(x)
assert( iscell(x) && (isempty(x) || sum(cellfun(@(y) ~ischar(y), x))==0 ), 'Input must be a cell array of strings.');
end
|
delta=[zeros(1,7),ones(1,50)];
n=-7:49;
y=filter(1,[1 -1.1],delta);
stem(n',y); |
function G = generalizationError(Xmat, Umat, Zmat, ratio )
% matrix sizes:
% Xmat D x N
% Umat D x K
% Zmat K x N
[ D, N ] = size(Xmat);
% unique assignment sets
Zmat = unique(Zmat','rows')';
N_assSets = size(Zmat, 2);
% randomly choose a number of dimensions
rperm = randperm(D);
myDims = rp... |
% Written by Patrick Strassmann
% Graphical representation of different potential outcomes on timing
% behavior following stimulatin--induced press inhibition
stimCondStarts = [50, 950, 1850, 2750, 3650, 7250, 50, 1850, 50, 1850]/100;
stimCondDurs = [500, 500, 500, 500, 500, 500, 1400, 1400, 1400, 1400]/100;
stimEndTim... |
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