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function [desiredaccel] = calculatedesacceleration(Pose, Twist, Control,ImpactParams)
%calculaterefacceleration.m Calculate a_ref for Recovery Controller
switch Control.recoveryStage
case 1
desiredaccel=Control.accelRef;
case 2
% desrdposn=[Impact... |
%hvintegrate - issue 1.2 (21/01/10)- HVLab HRV Toolbox
%-----------------------------------------------------
%[outdata] = hvintegrate (indata, exponent)
% Returns the cumulative integral of a function, or the cumulative VDV or
% MSDV of an acceleration time history.
%
% outdata = name of new HVLab data struct... |
function hdm05_setup_main (i_exp)
% ytc_setup();
opts.dataDir = fullfile('/scratch/dataset/HDM05') ;
opts.lite = false ;
liedb.lieDir = fullfile(opts.dataDir) ;
strFolder1 = ['lie20_half_inter' num2str(i_exp)];
[liedb] = readImdbTrain(liedb, opts, strFolder1,0);
mkdir(['../data/hdm05_' num2str(i_exp)]);
... |
% OL_ANT_SHS_MACRO_EXACT Open-loop ant stochastic hybrid system, exact population model
%
% This script performs a poopulation simulation of an SHS of ants. Rather
% than proceeding at uniform time intervals, it calculates the exact next
% time of an event. Consequently, events can be asynchronous.
clear all... |
function out = simulation_TA_center3(u)
global NUM_UAV NUM_TASK TASK_STATUS cnt
if isempty(cnt)
cnt =1 ;
end
num_data = 2*4+NUM_TASK*2+2 ;
for iter = 1 : NUM_UAV
wpt(1,(iter-1)*4+1:(iter-1)*4+4) = u((iter-1)*num_data+1:(iter-1)*num_data+4) ;
wpt(2,(iter-1)*4+1:... |
function [ W ] = pca(training_data, alpha)
%PCA Returns the principal components in the form of a matrix according to
%the second parameter, alpha, which dictates the energy willing to
%sacrifice.
% W = PCA(training_data, alpha) will return the principal components of
% the training data.
num_features = size(train... |
function[]= DTmain()
loadData;
disp('Training your model...');
mdl=DTtrain(trainData, trainLabels);% this function trains your model based on the train data and train labels
disp('Done training');
disp('Please enter the depth: ');
depth=input(' ');% asking the user to enter the desired depth
disp('prunning...');
mdl... |
%main program
%Kevin Phillips
clear all, close all, clc
%%
%load the corrupted data
load('ProjectMLKnew.mat');
x = MLK_HighNoise;
y = MLK_LowNoise;
%%
%analyze the audio
spechighnoise = create_spectrum(Fs,x);
speclownoise = create_spectrum(Fs,y);
%plot High
figure();
subplot(2,1,1);
plot(spechighnoise(:,1),abs(sp... |
function [ qmdp ] = solve_qmdp( qmdp_belief_points, pomdp, Q )
% iterate over the states
% qmdp_belief_points is the number of different beliefs we will
% sample to determine the optimal policy
for k=1:pomdp.nrStates
% j is a counter to iterate over different
% equally ... |
addpath('Z:\code\stickman')
addpath('Y:\008 Uncertainty Study')
% useful plot tools
plotMarkers = ['x'; 'o'; '*'; 's'; 'd'; 'v'; '^'; '>'; '<'; 'p'; 'h'];
|
function Bigtf = EDB2plotstackedTFs(firstirfile,nfiles,offset,nfft,typeofir,startsample,endsample)
% EDB2plotstackedTFs - Plots a number of TFs in a stacked way.
%
% Input parameters:
% firstirfile The data file containing the first IR file
% nfiles The number of files
% offset The numerical... |
function output_img = myConv2(input_image, myfilter, padding_method)
% input_image : noisy input image (type: double)
% myfilter : filter kernel to be used for convolution (type: double)
% padding_method : string that specifies the type of padding method to be used
% output_img : output image (type: double... |
% Generate Paramater maps based on a template of white matter/grey matter
% segmentation.a
w=lightbox('/home/hernan/matlab/spm8/apriori/white.nii');
g=lightbox('/home/hernan/matlab/spm8/apriori/grey.nii');
c=lightbox('/home/hernan/matlab/spm8/apriori/csf.nii');
t1map = 900 * w + 1400*g + 2800*c;
flowmap = 20 * w + ... |
basedir = '/Users/tomas789/Desktop/zadani1';
fid_cr = fopen([basedir '/cr.txt']);
fid_eu = fopen([basedir '/eu.txt']);
read_cr = fscanf(fid_cr, '%d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d', [23 inf]);
read_eu = fscanf(fid_eu, '%d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d... |
function Enhancement_Noise_Struct = compute_enhancement_noise_priors_from_background_ROIs(background_ROIs_Struct, largest_slice_ROIs_Struct, varargin)
Enhancement_Noise_Struct = [];
MRI_dir = '~/Data/Breast_MRI/Oxford/Matlab_Data';
plot_figs = 1;
fontsize = 8;
num_subplot_rows = 4;
num_subplot_cols = 5;
if length... |
function imgout = pshift(imgin, rshift, bshift, gshift) %#ok<INUSD>
%PSHIFT shift red, blue, and green channels in x and y directions
%
% PSHIFT(image, [rX, rY], [bX, bY], [gX, gY]) shifts the red channel in
% image by rX pixels in the x direction (right is +x) and by rY pixels in
% the y direction (down is... |
function fix_block2_distra_faces
% Due to a typo, the position of the target and distractors in all blocks 2
% of the distractor_faces conditions for the first three subjects (S54, S57
% & S65) was misplaced. This scripts 'corrects' this typo by changing the
% target position. Note, however, that the error in the cre... |
function varargout = detectpoint(varargin)
% DETECTPOINT MATLAB code for detectpoint.fig
% DETECTPOINT, by itself, creates a new DETECTPOINT or raises the existing
% singleton*.
%
% H = DETECTPOINT returns the handle to a new DETECTPOINT or the handle to
% the existing singleton*.
%
% DETECTPOI... |
%translate MS .car file to LAMMPS .data file
%atom_type atomic in LAMMPS
clc,clear,close all
%all the data below shoube be set yourself
infile='hBN.car';%name of input .car file
outfile='hBN.data';%name of output .data file
outfile_dir='D:\mathworks\car2data\'; %saving path
N_atom_types=2;%nu... |
% given a generic planar polygon computes the
% ray-polygon intersection. Polygon is a Nx2 set of samples
% with cyclic indexing (no repeated last element)
%
% WRITTEN 1 March 2010
function ray_t = ray_polygon_intersection( ray_p, ray_n, polygon )
DEBUG_MODE = 0;
if DEBUG_MODE
clc, clear, close all;
load ray_p... |
%% comparing intracellular fluxes
TestDataM=datasetM.val(2:end,:);
nMeas=size(TestDataM,2);
tempData=zeros(nMeas,nMod,numDels);
nMeasVec=findRxnIDs(model,datasetM.rxns);
cnt=1;
for i=1: length(Results)
if ~isempty(Results{i})
tempData(:,:,cnt)=Results{i}(nMeasVec,:);
cnt=cnt+1;
end... |
function [data, time, abstime, eventinfo, daqinfo] = daqread(filename, varargin)
%DAQREAD Frye lab version of the Data Acquisition Toolbox function to read
%customized (.daq) files
%
% This is a function for extracting data from spoof .daq files created on
% the Frye lab 2p system. Post-Matlab 2015 )using the session-b... |
while 1
try
imread('in.png');
run('ocr_pp');
delete('in.png');
fprintf('Restarting...\n')
pause(1);
catch err
%fprintf(getReport(err));
%fprintf('\n');
end
end |
function spec = calc_spec(HH, dH, f00, bp0, bp1, nub)
% B-phase spectrum calculation.
% parameters from spec_normal are used
% HH - mesh for calculation near the central field
% dH - intrinsic line width
% f00 if the generator freq
% bn_p - texture angle derivative in the center for B-phase spectrum
% nu... |
function D=featextpartial(root,imgname,T)
%load feature from bigger part of color images
rgbimg=imread([root filesep imgname]);
image=rgb2gray(rgbimg);
image=double(image);
%compare which is bigger, red or green?
edgeimg=loadedge(root,imgname);
numred=sum(sum(edgeimg(:,:,1)==200));
numgre=sum(sum(edgeimg(:,:,2)==200)... |
function TF =classiferExists(RootDir, varargin)
% Examines whether classifier exists on disk
%
% p = inputParser;
%
% p = addParamDefaults(p, 'runClassifier');
%
% addRequired(p, 'RootDir');
%
% parse(p, RootDir, varargin{:});
%
%
% modelPath = fullfile(p.Results.RootDir, p.Results.DataVersion, p.Resu... |
function [out_t,grad_t,grad_t_k] = f_x(x,p,i)
%% this inputs has the dimension numJoints*3 X 2
% only the current and delay ones are included
% th is the ypos height to have grf
% ypos is pre-calculated since it is easy to use gpuarray to achieve
% i is the index,less than half the grf is on the toe, more t... |
clear all;
%% Setup
NdtP = 20; % number of steps per period
Np = 0.25; % number of periods to compute
plotsol = 1; % (=1) plot mesh quality every time step
fmt = '-b'; % linetype for plotting mesh quality in time
N = 11; % Number of cells in y
M = 11; % Number of cells in x
absdisp = 1; % (=1) absolute... |
%Para ejecutar:
% Integracion_punto_Medio([0,1], 0.5, 8, @Ej_punto_medio)
%En donde los valores corresponden a:
% vector de valores iniciales, valor de h, numero de puntos, funcion
function solucion = Integracion_punto_Medio(xini, h, N, f)
D = length(xini);
x = xini(1);
y = xini(2:D);
solucion ... |
clc
clear all
close all
a=imread('zoneplate.png');
%First level decomposition
[p q r s]=dwt2(single(a),'db1');
b=[uint8(p), q; r,s];
%Second level decomposition
[p1 q1 r1 s1]=dwt2(p,'db1');
b1=[p1,q1; r1, s1];
b2=[uint8(b1), q; r s];
imshow(b2)
|
function [rho,f0] = invAbel5(x,F0,N)
% 1D Abel inversion algorithm based on direct evaluation of the inversion
% integral (see [http://mathworld.wolfram.com/AbelTransform.html] and [http://en.wikipedia.org/wiki/Abel_transform])
%
% Input Arguments:
% x -- abscissa vector for the input vector F0 (x and F0 ha... |
classdef overlap_block
% an object that contains the overlapping blocks used by
% expanding_block
properties
pixel % pixel{n} contains the pixels of the nth block
avg_gray % avg_gray(n) = mean( elements in pixel{n})
variance % variance(n) = mean( (pixel{n} - avg... |
function [vidoutput] = demo( )
vidoutput='';
reqToolboxes = {'Computer Vision System Toolbox', 'Image Processing Toolbox'};
if( ~checkToolboxes(reqToolboxes) )
error('detectFaceParts requires: Computer Vision System Toolbox and Image Processing Toolbox. Please install these toolboxes.');
end
s1=evalin('base','z1');
s2... |
% Benutzung des Matlab-Programmes:
% 1. eine nxn Matrix A definieren. Name muss A sein
% 2. Script ausführen.
dA = size(A);
B=A;
[L,U,P] = lu(A);
% Testen auf n x n Matrix
if dA(1) ~= dA(2),
display('A ist keine n x n Matrix!')
return;
end
lower = eye(dA(1));
upper = zeros(dA(1));
% Transformation durchführ... |
%#codegen
function val = mc_gadget_transmit(pin,pot_value )
val=0;
val =coder.ceval('IRTransmit',pin,pot_value);
end
|
% frequency_mathching: Compute the frequency of occurence of a set of outcomes
%
% Ex:
% TI=channels;
% O.N=5; % Number of conditional points
% [H,Oout]=frequency_matching(TI,O);
%
% See also mps_template
%
function [H,O]=frequency_matching(TI,O);
if nargin<1;
TI=channels;
TI=TI(2:2:end,2:2:end);
O.N... |
function [nr,zr,s21c] = LotsSmallLines_RandomUC_COMSOL_13Feb15...
(param,plotFlag,NbLines,freq)
ModelUtil.remove('Model');
ModelUtil.clear
import com.comsol.model.*
import com.comsol.model.util.*
model = ModelUtil.create('Model');
ModelUtil.showProgress(true);
model.param.set('L', '0.2[m]');
model.param.set('H'... |
function T = import_csvfile2table(filename,formatStr)
%% get data
fid = fopen(filename,'r');
% formatStr = '%s%s%d%d%f%f%s%[^\n\r]';
dataArray = textscan(fid, formatStr, 'Delimiter', ',', ...
'HeaderLines', 2-1, 'ReturnOnError', false);
fclose(fid); % Close the text file.
dataArray(end) = [];
%% find w... |
function [A,Q,G]=tmvar(PyArea,np,pt,s)
% computes MVAR parameters from trial data
%
% PyArea..........: trial data (nd x tr x nb)
% np..............: model order
% pt..............: quasi-stationary window size
% s...............: shift
if nargin<3, pt=size(PyArea,3); end
if nargin<4, s=floor(.5*pt); else, s=floor(s);... |
close all
%clear all;
%The system
k11 = 2; k12 = 1; k21 = 1; k22 = 2;
K = [k11, k12 ; k21 , k22];
% case 1
%L1 = 150; o1 = 30; L2 = 80; o2 = 0;
% case 2
%L1 = 80; o1 = 50; L2 = 150; o2 = 50;
% case 3
L1 = 20; o1 = 0; L2 = 100; o2 = 0;
%symmetric costs
c1 = 1; c2 = 1;
%asymmetric costs
%c1 = 1; ... |
%% EE6013_A5_P1.m
%% Clean Up
clear all;
close all;
clc
warning('off','all')
warning
% id = 'MATLAB:nearlySingularMatrix';
%% Variables
eq = 9;
initialX = [-4; 1];
soln = [-pi/2; pi];
maxIteration = 35E3;
iterations = 1:maxIteration;
gradient = [2; 3];
hessian = [3, 0; 0, 4];
dt = zeros(1,eq);
val = zeros(1,e... |
classdef (InferiorClasses = {?matlab.graphics.axis.Axes}) MPlot4D < handle
% this is a more powerful but less polished version of MPlot3D. It can
% accept arrays of dimension 5 and make videos that run over the 5th
% dimension. The constructor requires an array xData, which is the physical
% values ascr... |
%% This function groups the TRAINING faces according to their ages.
% ret: a KxN matrix with each column contains a 8x1 vector of elements 0,
% 1, 2 or 3. 0 means no face at this age group, 1 means train1 has one face
% at this group and similarly for 2. While 3 means both train1 and train2
% have faces at this gro... |
function [ varargout ] = chg0( nday,varargin )
% chg0 give the change of a sequence
% nday 计算n日涨跌幅，nday>0前验，nday<0后验
% varargin time sequence
%version 1.0, luhuaibao, 20140603
nseq = length(varargin);
for i = 1:nseq
if nday>0
seq = varargin{i};
%% 计算diff(seq)，前推nday天
... |
function [ gy ] = fetch_expression( y, genes, gene )
gy = y(:, strcmpi(genes, gene) );
end
|
function [WingPlanformX,WingPlanformY,Chord,Wing_Span,Cr,Ct] = PlanformGenerator(SurfaceArea,Span,gammaLE,gammaTE,RootChord,crank_location,crank_angle)
%PLANFORM GENERATOR
%OCdt Wells, RF 28125; Aero Class of 2020
%This function generates the planform of the wing, so that it can be used to find the chords at each wing ... |
clc; clear;
str={'a', 'b', 'c', 'ç', 'd', 'e', 'f', 'g', 'h', 'k', 'l', 'm', 'n', 'o', ...
'r', 's', 'þ', 't', 'u', 'v', 'y', 'z' 'B' 'E' 'F' 'P' 'Y'};
word=[ ]; word2=[]; comp=[]; empty=[]; leng=[]; grtleng=[]; ornek=[]; ornek2=[]; leng=[];
platon=imread('Platon.jpeg');
gray=rgb2gray(platon);
thresh=graythresh(... |
function [ diag_sum ] = spiral_diag_sum( n )
c=0;
if mod(n,2)==0
n=n+1;
c=1;
end
X=zeros(n);
for j=1:(n+1)/2
X(j,end-(j-1):-1:j)=(n-2*(j-1))^2:-1:(n-2*(j-1))^2-(n-2*(j-1))+1;
X(j+1:end-(j-1),j)=(n-2*(j-1))^2-(n-2*(j-1)):-1:(n-2*(j-1))^2-2*(n-2*(j-1))+2;
X(end-(j-1),end-(j... |
%% The MNIST dataset of handwritten digits
% Demonstrates loading the <http://yann.lecun.com/exdb/mnist/ MNIST dataset>.
%
% <https://github.com/opencv/opencv_contrib/blob/3.1.0/modules/datasets/samples/or_mnist.cpp>
%
%% MNIST dataset
% download/extract files if needed
dirMNIST = fullfile(mexopencv.root(), 'test', 'm... |
function test_fft
im_dir = '../faces/';
im = imread([im_dir 'c001.jpg']);
%%
im_fft = fft2(im);
nPts = 390; %length(im(:));
%
% ridxs = randperm(nPts);
R = abs(im_fft(1:nPts, 1:nPts));
theta = angle(im_fft(1:nPts, 1:nPts));
theta = reshape( theta(randperm(nPts * nPts)) , nPts, nPts);
Z = R .* exp(1i * theta);
i... |
function dydx=grad_II(x,y)
dydx=nan(size(y));
for i=2:length(y)
dydx(i,1)=(y(i)-y(i-1))/(x(i)-x(i-1));
end
end |
% This is the Two-Resistance Mechanism attribution method for T2
% edited on 4/3/20
function [Diff_T2,...
Rn_str_ref, Grnd_ref,ro_ref,ra_ref,rs_ref,f_TRM_ref,...
Rn_str_sel, Grnd_sel,ro_sel,ra_sel,rs_sel,f_TRM_sel,...
ra_prime_ref,f_2_TRM_ref,...
ra_prime_sel,f_2_TRM_... |
function res = commutatorSE3(u,v)
%This method computes the commutator [u,v] = [(u1,u2),(v1,v2)] =
%(u1 x v1, u1 x v2 - v1 x u2).
u1 = u(1:3);
u2 = u(4:end);
v1 = v(1:3);
v2 = v(4:end);
res = zeros(6,1);
res(1:3) = hat(u1)*v1;
res(4:end) = hat(u1)*v2 - hat(v1)*u2;
... |
function [area] = workingArea(l1,l2,l3,theta1_min,theta1_max,theta2_min,theta2_max,theta3_min,theta3_max)
%Working Area using Green Theorem
%Inputs: L1, L2, Theta 1 min,Theta 1 max, Theta 2 min, Theta2 max
%Return: The working area
close all
% 1st path: q1 = min, q2 = min, q3 = var -- Done
% 2nd path: q1 = min, q2 =... |
addpath('~/HELPFUN');
addpath('/mnt/disk1/ImageNet1M');
addpath('/mnt/disk1/ImageNet1M/ImageNettiny');
%load('sample_anchor_graph.mat')
%sZ = Z;
load('mean.mat');
%load('anchor1000.mat');
load('ILSVRC2012_caffe_CNN.mat')
%nbits = 128;
%load([num2str(nbits) '.mat'])
%sB = Z;
traindata = bsxfun(@minus, traindata, m);
... |
function [ bitStream ] = LDPC_decoder_hard( bitStream_enc, H )
%LDPC_DECODER_HARD Decode LDPC encoding.
% Decode LDPC encoding using a hard decoding scheme. This method should
% go fast and be pretty optimized.
[c_num,v_num] = size(H);
bitstrm_enc_rshp = reshape(bitStream_enc,v_num,[])';
H ... |
%%%Data Engine%%%
TorqueMax=7700; %[Nm]
ThrustMax=23000; %[N]
AoAMax=18; %[deg]
AoAEffective=12; %[deg]
RPMMax=6400; %[RPM]
RPMEffective=6400; %[RPM]
TorqueCoefficientUP=0.119615; %[Nm/rpm]
TorqueCoefficientDOWN... |
function [s, range, select] = srf(this, time, varargin)
% srf Shock response functions, first-order solution only.
%
% Syntax
% =======
%
% S = srf(M,NPer,...)
% S = srf(M,Range,...)
%
% Input arguments
% ================
%
% * `M` [ model ] - Model object whose shock responses will be simulated.
... |
function stm=stm(A);
L = eig(A);
n=length(A);
I=eye(n);
o=ones(n);
H=zeros(n,n);
for i=1:n-1
G(:,i)=L.^i;
end
H=[o(:,1),G];
for i=1:n-1,
if L(i)==L(i+1),
for j=1:n,
H(i+1,j)=(j-1)/L(i+1)*H(i+1,j);
end
else
end
end
K=inv(H);
m=n*n;
for j=1:n
for i=1:n:m
L1(j,i+j-1)=L((i+n-1)... |
function [Wi,Wo] = nc_winit(Ni,Nh,No,range,seed)
%NC_WINIT Neural classifier weight initialization
% [Wi,Wo] = nc_winit(Ni,Nh,No,range,range,seed)
% Uniform weight initialization
% Input:
% Ni: no. of input neurons
% Nh: no. of hidden neurons
% No: no. of output neurons
% range: weight initia... |
function E = feature_energy(window)
E = (1/(length(window))) * sum(abs(window.^2));
|
function output = round2Ndecimals(input, N)
output = round(input * 10^N) / 10^N;
end |
%将处理后的数据进行PCA投射
function[data_new]=Q2_step2(data,T) %T=0.9
% data=data_354;T=0.9;
[n,dim]=size(data);
std_data=std(data); %标准差
mean_data=mean(data); %平均值
for i = 1:dim
data_norm(:,i) = (data(:,i) - mean_data(:,i))/std_data(:,i);%标准化data
end
Cdata=corrcoef(data_norm); ... |
clear
clc
d1=dlmread('fit.txt');
tam=size (d1)
np=tam(1,1)
d2(1,1)=0
d2(1,2)=0
d2(2,1)=100
d2(2,2)=0
%figure(1)
plot(d1(:,1),d1(:,2),'-k')
hold on
plot(d1(:,1),d1(:,3),'*b')
hold on
plot(d2(:,1),d2(:,2),'-r')
axis([0 100 -250 250])
|
input = outvec;
% input = [0 64;
% .04 40;
% .04 44;
% .04 47;
% .1 59;
% .20 64;
% .24 40;
% .24 44;
% .24 47;
% .3 59]
fileout = 'run_2';
time = input(:,1)*tscale;
notes = input(:,2);
y_sound = zeros(100,2);
M=size(i... |
function [ Aout ] = MPO_Reshape( A, dir1, dir2 )
%reshape an MPO in 'dir1' orientation to 'dir2' orientation
%dir1, dir2 can be 'left', 'right', 'up', 'down'
if strcmp(dir1, 'down') || strcmp(dir1, 'up')
[~, N] =size(A);
else
[N, ~] = size(A);
end
if strcmp(dir2, 'down') || strcmp... |
function w = power(w,p) % w.^p
w = tospace(w); % only makes sens in space
for i = 1:length(w.coarse)
w.coarse{i} = w.coarse{i}.^p;
end
for i = 1:length(w.wav)
for m = 1:length(w.wav{i})
w.wav{i}{m} = w.wav{i}{m}.^p;
end
end
end |
%% This function will calculate the Lift Curve Slope for both the horzontal and vertical tails.
% The tail aerodynamic analysis is calculated using the same methods as for
% wing lift analysis. However the following assumptions are taken into
% account: The fuselage spillover factor may be ignored for a horizontal
... |
%% Maximizing Expected Prediction Error (MEPE)
%Liu, Haitao, Jianfei Cai, and Yew-Soon Ong. "An adaptive sampling approach for kriging metamodeling by maximizing expected prediction error."
%Computers & Chemical Engineering 106 (2017): 171-182.
function x_new = MEPE_function(obj,A,strategy)
% Details: Starting function... |
function logchaos
clf
hold on
% each time through the loop we try a different value of r
for r=2.4:0.01:4.0
% compute the first 50 values of the sequence
V = logmap(r, 0.5, 50);
% trim off the first 10 values
V = trim(V, 10);
% make... |
function result = dF_Ffunc( data, T_baseline, fluo_bg_idx )
%DF_RFUNC deltaF/F0 calculation for 5D data of the format CXYZT
%
datasize=size(data);
% reshape data into tRT size
data=reshape(data,[datasize(1),prod(datasize(2:4)),datasize(5)]);
% f0 has no T dimension, so repmat for - operation
f0=repmat(mean(data(:,:... |
%%
[pxx,f]=pmtm(NC,4,[],1000);
PXX{k}=pxx;
subplot(1,2,1)
px=mean(pxx,2);
s=semilogy(f,(px),'Color',myColorMap(k,:),'LineWidth',2);
xlim([0 300])
%%
Fline=[31 32 33.2 34 66.4 99.6 166.5 232.9];
%Fline=[ 33 ];
%
% %[NC] = ft_notch(NC, Fsample,Fline,20,0.5);
% [NC] = ft_notch(NC, Fsample,Fline,0.5,0.5);
%
nu1=50;
... |
close all ;
% Data from onlyincluded prior2normal
% 'D:\MaggiesFarm\2019_04_17_MF_dev_explore\data_thompson_mod12_new.xlsx'
tmp = load('datathompsonmod12.mat');
data = tmp.datathompsonmod12;
clear tmp;
ID = data.ID(2:end);
age = data.age(2:end);
const_SH = data.ConsistenSH(2:end);
const_LH = data.Consi... |
% Relative_Strength_Index Strategy
%if RSI<30: signal for buy
%if RSI>70: signal for sell
function [Profit,AccumulatedProfit,NumTransaction]=Relative_Strength_Index(Period,InitialBank,Commission,Equity)
% matlab functtion: rsindex %14 periods
Price=Equity;
DiffPrice=diff(Price);
DiffPrice=DiffPrice(:,1); %closing p... |
% ========== MCMC implementation for project ========== %
% Importing the stock prices
prices = xlsread("Price History_Commonwealth bank.xlsx", "Sheet 1", "B12:B2210");
% Converting the prices to returns
prices_shifted = [NaN;prices(1:end-1)];
returns_full = log(prices./prices_shifted);
returns = returns_full(2:end)... |
function [ x_gamma, y_gamma , x_gs, y_gs ] = getGammaProfiles(X, Y, D, xx, yy)
% function getCrossProfiles(X, Y, D)
% returns cross profiles from dose matrix <D> at location x = <xx> and y
% = <yy>
%
% By Dustin Jacqmin PhD, Medical University of South Carolina
x_gamma = interp2(X,Y,D,X,yy);
y_gamma = interp2(X,Y,... |
% BME313L_Lab7_P3_ShaoPoHuang
% This program will calculate the eigenvalues and eigenvectors for a given
% system of equations relating Sr-90 concentration to time in five
% different lakes and generate a combined plot
clear; clc; close all; % clears variables and console, close all figures
k = 0.69315/28.8; %... |
function generate_images(config, image_type)
listAudioFiles = dir([config.dir_audios, '*.wav']);
nAudios = length(listAudioFiles);
%%%%%%%%%%%%%%%%%%
% For each audio %
%%%%%%%%%%%%%%%%%%
for n=1:nAudios
fprintf("\n============================");
fprintf("\nAudio %d / %... |
function [K_vec, error] = ...
validationCurve(X, max_iters);
% K_vec: values of number of centroids.
% error: error of the model.
% X: X train set.
% max_iters: maximum number of iterations
K_vec = [2 3 4 5 6 7 8]';
error = zeros(length(K_vec), 1);
for i = 1:length(K_vec)
K = K_vec(i,1);
fprintf... |
% using Meakin 2013 formulation for BIR-8 pulses
% units are seconds, cm, radians, Gauss
% this version is trying to simplify to BIR 4
clear all
close all
clc
Npoints = 250;
Tseg = 2e-3; % seconds
Tgap = 100e-6;
t=linspace(0,Tseg,Npoints);
gamma = 2*pi*4.257e3; % rad/s/gauss
zeta = 15;
kappa = atan(60); % 1.5541;
t... |
function matUpdateOutputResult( obj, time, fphys2d, fphys3d )
%MATUPDATEOUTPUTRESULT Summary of this function goes here
% Detailed explanation goes here
for m = obj.Nmesh
obj.outputFile2d(m).outputIntervalResult( time, fphys2d{m}(:,:,obj.outputFile2d(m).varIndex) );
obj.outputFile3d(m).outputIntervalResult( ... |
function saveImgtoTxt(folder,savefolder , txt_name, test_id_num)
% folder % the path where mat files are saved
% savefolder % the path save the txt files
% txt_name: base name for save the text files
if ~exist(savefolder,'file')
mkdir(savefolder)
end
filenames = dir(folder);
filenames_new = filenames(3:end);
f... |
function [W, H, cost] = lnmf(V, num_basis_elems, config)
% lnmf Decompose a non-negative matrix V into WH using Local NMF [1] by
% minimizing the KL divergence. W is a basis matrix and H is the encoding
% matrix that encodes the input V in terms of the basis W.
%
% Inputs:
% V: [non-negative matrix]
% m-by-n n... |
% small_parallel_hwfet_in.m ADVISOR 2003-00-r0116 input file created: 21-Feb-2014 21:16:19
global vinf
vinf.name='small_parallel_hwfet_in';
vinf.drivetrain.name='parallel';
vinf.fuel_converter.name='FC_SI41_emis';
vinf.fuel_converter.ver='ic';
vinf.fuel_converter.type='si';
vinf.torque_coupling.name='TC_DUMMY';
vin... |
%2012 12 1 by lichao
%产生渐变数据，以便微透镜成像观察
clc
clear all
close all
N=101;
d=30;
data_grad=zeros(N);
for i=1:N
data_grad(i,:)=mod(i,d);
end
figure
imshow(data_grad,[])
save data_grad data_grad |
%対応点の計算と決定
%点間の距離判定を行い、最近傍点を対応点に決定する
%GPAまたはICPの場合
%Initialize----------------------------------------------------------------
clear all
clc;
tic;
%Set parameter-------------------------------------------------------------
sample = 200;
landNo = 17;
%GPAのとき
inLand = 'alignLand/alignland%d.xls';
inVec = 'moveData/ali... |
%% get_id_orthoptera
% gets id of species name in Orthoptera Species File Online
%%
function id = get_id_orthoptera(my_pet, open)
% created 2021/08/13 by Bas Kooijman
%% Syntax
% id = <../get_id_orthoptera.m *get_id_orthoptera*>(my_pet, open)
%% Description
% Gets identifier for Orthoptera Species File Online
%
% In... |
function [f,t,YMat] = FFT_sliding_window(y, Fs, windowSize, stepSize)
%
% y: the signal to compute FFT on.
% Fs: sampling rate in Hz.
% windowSize: time of window in which to compute FFT in seconds.
% stepSize: how far to move in seconds before each successive FFT.
%
%
% DHO, 3/08
%
windowSize = windowSize*Fs;
stepSi... |
function [Xnew, err]= line_linearSolve(Li, Lj, Omega, X)
x=zeros(12,1);
x(1:3)=X(1,1:3)';
x(4:6)=X(2,1:3)';
x(7:9)=X(3,1:3)';
x(10:12)=X(1:3,4);
H=zeros(12,12);
b=zeros(12,1);
err = 0;
for k = 1:size(Li)(2)
A=zeros(6,12);
li = Li(:,k);
lj = Lj(:,k);
wi = Li(1:3,k);
di = Li(4:6,k);
... |
function [y, total, sum_ti, sum_tz] = nnconv( x, f , b, stride, pad, threshold)
%UNTITLED4 Summary of this function goes here
% Detailed explanation goes here
% x = h * w * c * n;
% f = fh * fw * fc * k;
% y = yh * yw * k * n;
% yh = ((h - (fh-1)) + 2*pad) / stride
% yw = ((w - (fw-1)) + 2*pad) / stride
% global to... |
function res = lorenz()
[T, M] = ode45(@rate_func, [0 30], [1 2 3]);
X = M(:,1);
Y = M(:,2);
Z = M(:,3);
comet3(X,Y,Z);
end
function res = rate_func(t, V)
x = V(1);
y = V(2);
z = V(3);
sigma = 10;
b = 8/3;
r = 28;
dxdt = sigma * (y-x);
... |
function sig=noise3(beta, n)
%sig=FractRnd(beta, n)
%To generate 1/f^betta noise
%INPUT
% beta is the exponent, a number
% n is the number of synthetic data points
%OUTPUT
% sig is an n-points array
%
len_beta=length(beta);
phi_n=2*pi*rand(1,n);
%[B,A] = butter(10, 0.2);
%phi_n=filter(B,A,phi_naa);
f=[1:n].^(... |
function [H,SS,Q] = getPCRegression(Z0,Z1,Z2,X0,X1,X2,ts)
%GETPCREGRESSION Returns per-channel regression for lagged samples onto average PC
%
% [H,SS,Q] = kal.getPCRegression(Z0i,Z1i,Z2i,X0,X1,X2,ts);
%
% Note: this function is redundant and is just for the sake of explicitly
% enumerating how steps are proce... |
function rtstruct = getRtStructForPlan(patient, planUid)
%GETRTSTRUCTFORPLAN [please add info on me here :<]
if ~patient.planReferenceObjects.rtstructsForPlan.isKey(planUid)
rtstruct = [];
return;
end
rtstruct = patient.getDicomObject(patient.planReferenceObjects.rtstructsForPlan(planUid));
... |
%If one continuous bond, as identified by watershed segmentation, touches
%more than 2 grains, this script identifies which bond voxels belong to
%which grains
function [GrainPair,CCbonds]=multigrain(bondnum,CCbonds,labelgrn) %Function to separate bond areas in the case of >2 grains per continuous bond.
Separated=[0 ... |
function S=s_minus(A,B,C,D,dc,tol)
%S_MINUS Stable Strongly Controllable Geometric Subspace
%
% S = s_minus(A,B,C,D[,dc])
%
% computes a matrix whose columns span the geometric subspace
% S^{-} for a system characterized by (A,B,C,D).
%
% Note that by default or if dc = 0, the... |
fid = fopen('clean.txt');
tline = fgetl(fid);
count=1;
full=1:25;
Adjacency=[];
while ischar(tline)
tline = strip(tline);
tline_split=split(tline,' ');
tline_split=str2double(tline_split);
A = ismember(full,tline_split);
Adjacency=[Adjacency A'];
tline_split=[];
tline = fgetl(fid);... |
function this = draw(this, name, type, pos, size, value, cb)
import AMF.*
control.name = name;
control.type = type;
control.pos = pos;
control.size = size;
control.callback = cb;
control.value = value;
control.selected = '';
this.controls.(name) = control;
this.dim(1) = max([control.pos(1) + control.size(1) + 2, th... |
function [datamatrix] = generateDataMatrix(num_sensor,num_slot)
datamatrix=zeros(num_sensor,num_slot);
for i=1:num_sensor
start=(num_slot-(num_slot/4))*rand;
start=ceil(start);
size=(num_slot*4)/rand;
size=ceil(size);
ending=start+size;
for j=1:start
datamatrix(i,j)=0;
end
... |
function [ allS,cm,allP,unq,allL ] = looMMC(sp,grp)
%looMMC - leave one pixel out cross validated MMC
%
% For the spectral data and its groupings, we need to iteratively perform
% leave one pixel out MMC and then predict the left out pixel. Perhaps by
% default we will use 3-nearest neighbours. Also try to present the
... |
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