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function [ positions,pnl,action ] = backtest( p,spread,beta,lambda )
%BACKTEST Summary of this function goes here
% Detailed explanation goes here
positions=zeros(length(p),2);%持仓
pnl=zeros(length(p),1);%每日损益
action=zeros(length(p),2);%买卖操作
action=action*NaN;
upperlimit=mean(spread)+std(spread,1)*lambda;%上界
lowerlimi... |
function [xf, Pf, xp, Pp] = nonLinearKalmanFilter(Y, x_0, P_0, f, Q, h, R, type)
%NONLINEARKALMANFILTER Filters measurement sequence Y using a
% non-linear Kalman filter.
%
%Input:
% Y [m x N] Measurement sequence for times 1,...,N
% x_0 [n x 1] Prior mean for time 0
% P_0 [n x n] Prio... |
function sbmlv23_edited = sbmlv23_modifications(sbmlv23_unedited, list)
sbmlv23_edited = sbmlv23_unedited;
sbmlv23_edited.mets = correct_metsNaming(sbmlv23_edited.mets);
%first modfications done to sbmlv22
sbmlv23_edited = sbmlv22_modifications(sbmlv23_unedited);
%***************************... |
%% s_barWidthTest
%
% This is just a test scritp. Nothing special.
%
% (HJ) April, 2014
%% Init
wave = 400:10:700;
sceneSz = 1200;
fov = 1;
vDist = 1;
pupilDiameterMm = 3;
%% Create scenes
param.sceneSz = sceneSz;
param.offset = 0;
param.barWidth = 1;
param.barReflect = 1;
param.bgReflect = 0.1;
scene = sceneCreat... |
function flag = isOutOfBound(row, col, imageSize)
flag = not(floor(row) >= 1 & ceil(row) <= imageSize(1) & floor(col) >=1 & ceil(col) <= imageSize(2));
end |
function KPart = lin_kernelDiffX(X, theta, q);
% KERNELDIFFX Compute the gradient of the kernel with respect to X.
% Since the result is all zeros apart from one row/column combination,
% and the result is symetric, here we return a matrix whose rows are the
% vectors which give the row/column combinations
theta =... |
% Ruben Hinojosa Torres, Jianai Zhao, CSCI 1320
%==========================================================================
load('raw.mat');
raw = Raw;
clear Raw
[r1,~,~] = size(raw);
%Greatest number of tweets in state.
%max task3(Filename,Row where the data starts (tweets), Column where the
%states are)
[~... |
classdef Filter < dagnn.Layer
properties
pad = [0 0 0 0]
stride = [1 1]
dilate = [1 1]
end
methods
function set.pad(obj, pad)
if numel(pad) == 1
obj.pad = [pad pad pad pad] ;
elseif numel(pad) == 2
obj.pad = pad([1 1 2 2]) ;
else
obj.pad = pad ;
end
... |
%%%%%% maybe the last banben
%%%%%%%%%%%%%% add the points from area 1,and then merge the samll areas.
%%%%%%%%%%%rhok > number(SS{i})
%%%%%%%%%%%%%cross-entropy
clear all
close all
clc
disp('The only input needed is a distance matrix file')
disp('The format of this file should be: ')
disp('Column 1: id of element i... |
function hw4_bin_img_reconstruction
clc;
disp('HW4');
load('projectionData')
n = size(sumR,2); % 20
m = 2*n-1;
I = zeros(n,n);
countOfIterations = 7;
countOfPairs = 6;
for i = 1:countOfIterations
for p = 1:countOfPairs
% CR
if p == 1
p1 = sumC;
p2 = sumR;
... |
function shank = electrodeFactory(name)
% This builds the probe files that we use to handle channel maps and
% filtering corrections
% if no argument is passed in, use the gui to choose from a list of options
if nargin == 0
shankList = {'Shank2', ...
'AcuteZif2Om32', ...
'MTSingleElectrode'... |
function kmh = ms2kmh(ms)
%ms2kmh - Convierte un valor en m/s en km/h
%
% kmh = ms2kmh(ms)
kmh = ms * 3.6;
end
|
img = imread('01.jpg');
img2 = zeros(size(img, 1), size(img, 2), 3, 'uint8');
for i = 1: size(img, 2)
for j = 1: size(img, 1)
x = cosd(45)*(i - 200) + sind(45)*(j - 150) + 200;
y = -sind(45)*(i - 200) + cosd(45)*(j - 150) + 150;
if(x >= 1 && x <= size(img, 2) && y >= 1 && y <... |
function newS=optimizeS(option,admmrho,Gamma,Z)
[U,Sig,V]=svd(Z+Gamma./admmrho);
[row,col]=size(Sig);
temp = zeros(size(Sig,1),size(Sig,2));
for i=1:row
for j=1:col
temp(i,j)=max(Sig(i,j)-option.mu/admmrho,0);
end
end
newS = U*temp*V';
end |
function h=ncreadandcat(files,vars)
% h=ncreadandjoin(files,vars)
% in
% files cell array, names of files to read
% vars cell array, names of variables to read
%
% out
% h h.vars{i} contains the variable, concatenated along the last dimension
for i=1:length(files)
[f,dims]=nc... |
%HVMAKESTRUCT - issue 1.1 (27/01/10) - HVLab HRV Toolbox
%-------------------------------------------------------
%[newtruct] = HVMAKESTRUCT(title, yunit, xunit, dtype, dxvar, stats, xvals)
% Creates a new empty workspace data structure array with fields in the
% required order
%
% newtruct = new workspace d... |
function a = kridgereg( K, y, gamma )
%kridgereg
%Input
%K - kernel (gaussina kernel in this case)
%y - y set
%gamma - ridge regression parameter
%Output
%a - dual weight vector
a=(K + gamma.*length(K).*eye(length(K)))\y;
end
|
function noMargin(axHandle)
% NOMARGIN
%
% Description:
% Expand the axes to fill figure window
%
% Syntax:
% noMargin(axHandle);
%
% Input:
% axHandle axes handle (default = gca)
%
% History:
% 3Mar2018 - SSP
% ------------------------------------------------------------------
if nargin == 0
axHan... |
function plotAverage(x,y,grps,cols)
% Unique groups
[unq,~,ind] = unique(grps);
numG = numel(unq);
h = zeros(numG,1);
% Correct for numeric grps
if isnumeric(unq)
nunq = cell(size(unq));
for n = 1:numG
nunq{n,1} = num2str(unq(n));
end
unq = nunq;
end
% Create new figure
figure('Position',[200... |
%-------------------------------------------------------------
% plik wczytujący wagi kryteriów
%-------------------------------------------------------------
% Hubert Gawryś 2014-03-16
% Instytut Zarządzania w Budownictwie i Transporcie (L-3)
% Wydział Inżynierii Lądowej
% Politechnika Krakowska im. Tadeusza K... |
function Spikes = Spike_Detector(dF,std_threshold,static_threshold)
%dF function is the first derivative where
%dF(ROI_index,Time,Multiple_Videos)
Spikes = zeros(size(dF,1),size(dF,2));
dev = std_threshold*std(std(dF));
avghx = mean(mean(dF));
for j = 1:size(dF,1)
for k = 1:size(dF,2)
droploc=... |
%%%%%%%%%%%%%%%%%%%%%%%%%%
% Driver function for catching simulation
% Micah Corah
%%%%%%%%%%%%%%%%%%%%%%%%%%
close all
clear all
disp('Beginning simulation');
rng('shuffle','twister');
t=clock;
step=0.0016;
%Sampling space
block_dir=rand(1)*pi;
%block_dir=2.0548;
block_u=[0;0.5;0.09];
block_nu=[rot([0;0;1],block_dir)... |
% evaluation - FBPConvNet
% modified from MatconvNet (ver.23)
% 22 June 2017
% contact : Kyong Jin (kyonghwan.jin@gmail.com)
clear
restoredefaultpath
reset(gpuDevice(1))
run ./matconvnet-1.0-beta23/matlab/vl_setupnn
load preproc_x20_ellipse_fullfbp.mat
load('./pretrain/net-epoch-151.mat')
% cmode='gpu'; % 'cpu'
cmod... |
function [p sc] = plotPRC_phases(conStren,Sphasez,PSphasez,NcS_sel,cmap)
p(1) = plot(conStren,Sphasez );
p(1).Color = [0 0 0];
p(1).LineWidth = 2;
p(1).LineStyle = '-';
hold on
sc(1) = scatter(conStren(NcS_sel),Sphasez(NcS_sel),75,cmap(NcS_sel,:),'filled');
sc(1).Marker = '^';
p(2) = plot(conStren,PSphasez );
p(2).Co... |
function dq = ODE_boundary_problem(x,q,theta,area_ann,dia_bit,dx,g,mu_mud,Cl)
% for source terms
% 2 - drillstring
% 1 - annulus
source_ann = source_terms(q,theta,area_ann,dia_bit,dx,g,mu_mud,1);
dq = [source_ann/Cl^2;
0];
end |
function y = stdsourcefile(x)
if x == 1
y = [196, 42, 220, 253, 131, 226];
end
end |
function package = ...
sharcnet_testingLoopPackage(dataset, patientList_training, patientList_full, ...
exerciseList, ind_exercise, param, exerciseCropLength, specialCommand, specialPackage)
if iscell(patientList_full)
% the testing array may be passed in as a cell array. if that's
% th... |
function [T1,T2] = SWAP(Ta,Tb)
LA = size(Ta,1);
LB = size(Tb,1);
if LB < LA
T1 = Tb;
T2 = Ta;
else
T1 = Ta;
T2 = Tb;
end
end
|
function dispstr=dispplane(valstr)
if (numel(valstr)<6)||(~strcmp(valstr([2,5,6]),''''',')) dispstr=['best fit plane through atom group ''',valstr(2:end-1),''''];
elseif strcmp(valstr(3),'3')
dispabbr=struct('a','atoms','r','Cartesian coordinates','c','direct coordinates');
temp=regexp(valstr,'[{}\[\],]','spl... |
function CLwing = VLMImplementation(Mach,Alt,span,Sweep,rootChord,fuseDia,taperRatio)
% clear all
% close all
% clc
% %
% taperRatio = 0.373;
% rootChord = 39;
% fuseDia = 27;
% Alt = 30000;
% Mach = 0.77;
% Sweep = 25;
% span = 262.5;
%% Start Point
%% Geo Setup
geo.fnx= [0,5]; %number of panels on flap chor... |
% BME313L_Lab4_P2_ShaoPoHuang
% This code will 1) determine various Thiele moduli corresponding to
% different efficiency values and 2) make a plot relating these two
% variables
clear; close all; clc; % clear existing values/console
N = 0.3:0.1:0.6; % vector of N (efficiency values)
Es = 0.03; % pre-specifie... |
%% =========== computing the eroor rate and accuracy =============
function counter = Test(layer,number_of_sampels,Train_or_Test,L,labels,dataset,tanh_or_sigmoid)
layer(1).a=dataset';
counter=0;
for num_in=1:number_of_sampels
for c=2:L
if c==2
layer(c).z = (layer(c-1).a(:,num_in))'*(l... |
function [f_cohr] = calc_fcohr(PDPMat_cut, dt)
P_T = sum(PDPMat_cut);
Tau = [0:1:size(PDPMat_cut,2)-1];
Tau_mean = sum(Tau .* PDPMat_cut)/P_T;
Delta_T = sqrt(sum(Tau.^2 .* PDPMat_cut)/P_T - Tau_mean^2) * dt;
f_cohr = 1/(2*pi*Delta_T);
end |
if accel_B(i,1) <= 0
traction;
Fv(i,1) = Fv(i,1)*u(i,1);
acc(i+1,1) = Fv(i,1)./mass;
if acc(i+1,1) > max_accel
acc(i+1,1) = max_accel;
end
elseif accel_B(i,1) > 0
braking;
Bv(i,1) = Bv(i,1)*u(i,1);
acc(i+1,1) = Bv(i,1)./mass;
if acc(i+1,1) < max_decel
... |
function time_out = time2pattern(time_in,resol)
%TIME2PATTERN convert input time vector to time patter (e.g. yyyymmdd)
%
% Input:
% time_in ... time vector (datenum) or time matrix
% resol ... string switch for output precission:
% 'day': yyyymmdd
% 'hour': yyy... |
clc;
clear all;
close all;
a=imread('images.jpg');
b=im2bw(a,0.5);
figure; imshow(b);
[m, n] = size(b);
w=[1,1,1; 1,1,1; 1,1,1];
reg=zeros(m,n);
reg(200,150)=1;
figure; imshow(reg);
imgcmp=~b;
figure; imshow(imgcmp);
while(true)
finalimg= imdilate(reg,w) & b;
if(finalimg==reg)
break;
end
... |
run('../util/import_data');
neg_sizes = [20; 35; 50; 70; 90; 110; 130; 150];
gda_far = zeros(8,1);
gda_frr = zeros(8,1);
svm_far = zeros(8,1);
svm_frr = zeros(8,1);
gtrain_far = zeros(8,1);
gtrain_frr = zeros(8,1);
strain_far = zeros(8,1);
strain_frr = zeros(8,1);
for z=1:8
NUM_NEG_TRAIN = neg_sizes(z);
run('.... |
publish('Untitled.m','doc')
winopen('html/Untitled.doc')
|
function load_mass_budget_rules
%% load_mass_budget_rules.m
global params
r = global_jess_engine();
r.eval(['(bind ?mass_budget_rules_clp "' params.mass_budget_rules_clp '")']);
r.eval('(batch ?mass_budget_rules_clp)');
r.eval(['(bind ?mass_budget_rules_clp "' params.adcs_design_rules_clp '")']);
r.eval('(batch ?mass_... |
function f = evalFunc2(grid)
% grid: a 9x9 matrix representing a complete grid
% initial_grid: a grid where all non zero elements are the initially fixed
% digits
% returns the number of digits appearing twice in the line/colum/square
% of the grid.
% If a digit appears three times in a same line/column/square, it wi... |
function [S_k, alpha_k] = update_active_set(S_k, alpha_k, v_k, gamma_k, gamma_max, is_aw)
% Active set update the weights alpha associated with the solution found at
% every iterate. Depending on weather an swap step is chosen or a fw step
% the update is different. For a good explanation please refer to the
% follwin... |
function W = fix_adc_jitter(W)
V = clip_channels(W);
% figure; plot(V)
X = get_channel_width(V);
for i = 1:NUM_CHANNELS
s = W(X(i,1)-BETA:X(i,2)+BETA);
width = X(i,2)-X(i,1)+1;
h = floor((X(i,1) + X(i,2))/2);
offset = h - STD_START - (i-1)... |
function res = opdracht_1_versie_1_CHECK(apStudentSol)
%%========== PLACE SOLUTION IN COMMENTS HERE
% % % % % % % wrijvingsKracht= [ 12 31 31; 123 124 14; 102 182 21];
% % % % % % % wrijvingsKracht((1,3))
% % % % wrijvingsKracht= [ 12 31 31; 123 124 14; 102 182 21];
% % % % wrijvingsKracht(1,3)
%%==========
%% FI... |
% demo_multiband_RF_pulse_design.m
% Written by Namgyun Lee
% Email: ggang56@gmail.com
% Created: 03/01/2017, Last modified: 03/01/2017
close all; clear all; clc;
%--------------------------------------------------------------------------
% Information about fremex05:
% amplitude range of am_fremex05: -163 <=> 32767 ... |
%% Extreme Learning Machine tutorial / improvements: change activation function
clear all
addpath datasets
folder = 'datasets\cifar';
%~0.577 with n=1000 and 5 ensemble
%%
n = 10000; % number of neurons
N = 10000;
O_ensemble = zeros(10,n,5);
w_ensemble = zeros(n,3072,5);
b = -1 + (2).*rand(n,1);
B = zeros(n,N);
for... |
function wM = oneStepMotors(Kt, R, Ke, IWheels, VM,wM,Tsample)
%UNTITLED5 Summary of this function goes here
% Detailed explanation goes here
BEMF = Ke.*wM;
T = (VM - BEMF)*Kt/R;
wM = wM + T./IWheels*Tsample;
end
|
f_s=3000;
t=(1:f_s)/f_s;
ff1=100;
ff2=400;
ff3=1000;
x=sin(2*pi*ff1*t)+sin(2*pi*ff2*t)+sin(2*pi*ff3*t);
figure;
subplot(211);plot(t,x);
subplot(212);hua_fft(x,f_s,1);
% y=filter(bz1,az1,x);
y=bandp(x,900,1100,800,1200,0.1,30,f_s);
figure;
subplot(211);plot(t,y);
subplot(212);hua_fft(y,f_s,1); |
function plot_sub(X,K,i)
% plot_sub(X,K,i)
% plot submatrix of K for element i=[i1 i2 i3] from the mesh X{1} X{2} X{3}
p=hexa_sub(X,K,i);
hexa_plot(p.X,p.X,p.S2);
|
timeperiod={{[0 100 900 1000]} {[1000 1200 2800 4000]}};
labels={'1sec'};
nomove='NO1';
immove='IM1';
ammove='AM1';
n_con_ex=6;
clear dm Res_in Res_out
code_louk_2_gen
gzerds1=ztype;
gdsR1o=Res_out;
gdsR1i=Res_in;
timeperiod={{[0 250 2750 3000]} {[3000 3250 5750 6000]}};
%timeperiod={{[0 250 3750 4000]} {[4000 4250 5... |
function [Si_a, Sti_a] = reorder(Si, Sti)
Si_a = Si;
Sti_a = Sti;
Si_a(1) = Si(12);
Sti_a(1) = Sti(12);
Si_a(2) = Si(13);
Sti_a(2) = Sti(13);
Si_a(3) = Si(1);
Sti_a(3) = Sti(1);
Si_a(4) = Si(2);
Sti_a(4) = Sti(2);
Si_a(5) = Si(4);
Sti_a(5) = Sti(4);
Si_a(6) = Si(5);
Sti_a(6) = Sti(5);
Si_a(7) = Si(8);
Sti_a(7) ... |
function qqSwap(varargin)
% twoQSwap: two qubits swap
% bias qubit q1 or q2, drive qubit q1 and q2, readout qubit q1 or q2,
% q1, q2 all has to be the selected qubits in the current session,
%
% <_o_> = qqQSwap('qubit1',_o|c_,'qubit2',_o|c_,...
% 'biasQubit',<_i_>,'biasAmp',[_f_],'biasDelay',<_i_>,...
% 'q... |
function varargout = dock(varargin)
varargout={};
try
if nargin>=1
switch length(varargin)
case 1
if isnumeric(varargin{1})
fignum = varargin{1};
f = figure(fignum);
elseif ischar(varargin{1})
figname = v... |
function xsol = odesol(fun,t,x)
%
% [xsol = odesol(fun,t,x)
%
% Risolve l'ODE y'(t) = fun(t)
%
% INPUTS:
% fun : campo vettoriale associato
% t : vettore di tempi in cui vogliamo calcolare la soluzione
% x : dato iniziale
%
% OUTPUTS:
% xsol : matrice le cui colonne s... |
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;
tmp = load('dataquestionnaire.mat');
data_quest = tmp.dataquestionnaire;
clear tmp;
%%% demo
ID ... |
function y= ef(l)
a=0;
b=2;
c=1;
K=((l-a)+sqrt((a^2)-2*a*l+(l^2)-4));
r=[K^2+(a-l)*(K^(-1)); c*K^(-1); 0];
M=[K^2+(a-l)*K, c, 0; c*K, b-l, c*K; 0, c, a*K+K^2];
x=r\M;
R=x(1);
X0=x(2);
T=x(3);
y=abs(R)^2+abs(T)^2;
end |
clear all;
run Settings.m
load clusters.mat
%create cluster vecs
u = unique(names);
vec=zeros(1,length(names));
for k=1:length(u)
ind=find(contains(names,u{k}));
vec(ind)=k;
end
a=double(jet);
ind=round(vec/length(u)*64);
col=a(ind,:);
%%
c=clusters;
A=zeros(size(c,2)-2);
algos=size(c,1); %number of cluste... |
function [avg_fft_open_1,avg_fft_open_2,avg_fft_close] = alpha_analyse(EEG, fs_new,dur)
EEG = pop_resample(EEG, fs_new);
EEG = pop_eegfiltnew(EEG, [],0.5,[],true); %HP filtering (Filter DC)
EEG = pop_eegfiltnew(EEG, [],20); %LP filtering
EEGfilt = EEG.data(1,:)';
strt = 16;
stp = strt+dur;
... |
function [subj] = raicar_rank (subj)
%
% function [subj] = raicar_rank (subj)
%
% Author: Zhi Yang
% Version: 2.0
% Last change: June 08, 2007
%
% Purpose:
% search through the CRCM, idenfy the aligned components and rank them by reproducibility
% Input:
% subj: subject object. The following input fie... |
function centroids = kmeans_mpi(data_slaves,centroids, N_slaves)
K=size(centroids,1);
% Master Broadcasts Centroids to slaves
for i=1:N_slaves
local_centroids{i} = centroids;
end
% Slaves run k-means on local data
for i=1:N_slaves
local_clusters{i} = kmeans_mpi_slave(data_slaves{i}, local_centroids{i});
end
... |
clear all, close all
figure('position',[2436 875 1120 600])
% subplot(211)
dc = load('~/Work/MITgcm/Downloads/dispersionCurve.mat');
load('ke_end.mat')
leg = cell(length(om),1);
hline = [];
cols = [0 1 0; 1 0 0];
desc = fileread('../description.txt');
subplot(211)
pcolor(dc.L,dc.sigs,log10(dc.P0P)');
shading flat
co... |
choice=5;
n=3;
A = [1 5 3 18 ;2 4 7 10; 4 6 2 50];
B=A(1:n,1:n);
% pivoting
for i = 1:n-1
[maxc , m]= max(A(i:n,i));
m=m+i-1;
A([i m],:)=A([m i],:);
end
B_real=A(:,n+1); % storing real constants B
PiA=A(1:n,1:n); % Pivoted Matrix of coefficients only
L=zeros(n); % set L to be a ... |
%{
-> acquisition.Session
cell_id: varchar(36) # a string identifying the cell in which this intracellular recording is concerning
---
cell_type: enum('excitatory','inhibitory','N/A')
-> reference.ActionLocation
-> reference.WholeCellDevice
%}
classdef Cell < dj.Manual
end |
function [ B ] = MPS_ReduceBondDim_left_sweep_down( A, B, rhol_B_B, rhol_A_B )
%pinv is used everywhere, not optimal.
[N, ~] = size(B);
fprintf('$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$\n');
fprintf('The error at position %i in sweep is %d.\n', N+1, normDifferenceBetweenStates_left(A,B));
... |
%
% Script for computation of average RDFs and CNs
%
% Directories to consider
dir_names = dir('seed_*');
dir_names = {dir_names.name};
ndirs = length(dir_names);
% All data
% Stresses
all_s_xx = zeros(ndirs, 20);
all_s_yy = zeros(ndirs, 20);
all_s_zz = zeros(ndirs, 20);
all_s_xy = zeros(ndirs, 20);
all_s_yz = zeros(... |
function [I_hyper,I_rgb,I_gt,g,G,extra,wl,wl_ori,Sel,s,bbl,H1] = ...
prepare_fusion_dataset(dataset, options)
%PREPARE_FUSION_DATASET Summary of this function goes here
% Detailed explanation goes here
if nargin < 2
options = [];
end
I_hyper = [];
I_rgb = [];
switch dataset
case {'pavia_nonrigid_algo','... |
function strengistreng = checkStrinstri( a,b )
n=size(a,2);
m=size(b,2);
strengistreng=-1;
for i=1:m-n+1
if checkString(b(i:i+n-1), a)
strengistreng = i;
return;
end
end
end
|
% test on efficient schur complement inversion
%clc; clear all; close all;
% B = B(:,1);
A = mmread('A.mm');
B = mmread('B.mm');
P = mmread('P.mm');
% figure; spy(A)
% figure; spy(P)
% e = eigs(A\(A+P),50,'lm');
% figure; plot(e)
% A = (triu(A,0) + tril(A.',-1));
% X = A\B;
% fprintf('%2.4g s\n', toc)... |
caseno = 1;
switch caseno
case 1
sys = tf(1,[1 2 1])*tf(1,[1 0]);
kp = 0.25;
ki_by_kp = 0.25;
leadlag = tf([1/0.5 1],[1/2 1]);
case 2
w1 = 8;
w2 = 2;
sys = tf(w1*w2,[1 w1 w1*w2])*tf(1,[1 0]);
kp = 0.25;
ki_by_kp = 0.25;
leadlag = tf([1/0.25 1],[1/1 1]);
end
cla... |
%% part 1
% part a
clearvars, close all;
dbstop if error;
testmat=zeros(64,128);
for j=1:size(testmat,2)
if j<=32
testmat(:,j)=10;
elseif j<75+32-10
testmat(:,j)=10+j-32;
else
testmat(:,j)=75;
end
end
imagesc(testmat)
colormap gray
% part b, plot brightness as a function of pos... |
function [new_sound_fields,new_sound_field_ids] = get_sound_features_v7(input_matrix,numfilts,post,type);
new_sound_fields = [];
new_sound_field_ids = {};
% sound_on = zeros(1,size(the_matrix,2));
% sound_off = zeros(1,size(the_matrix,2));
% a = find(diff(the_matrix(6,:))>0);
% b = find(diff(the_matrix(6,:))<0);
locati... |
% Leap Motion Data Processing Script
% Load raw data from text (ASCII) file
%Left hand raw data
Lraw = importdata('L3N',' ',1); %imports data and ignores first row (headers)
% Read coordinate data (PalmX, PalmY, PalmZ)
xL = Lraw.data(2000:3000,9);
yL = Lraw.data(2000:3000,10);
zL = Lraw.data(2000:3000,11);
% D... |
function [ftfj] = ft_fj(T, Td, J, Jd)
%% Parameters Description
% T, actual run time
% Td, Expected run time
% J, Jerk
% Jd, The rate of acceleration that passengers can accept
% ftfj, 时间惩罚与舒适度惩罚之积
%% main
% clear; clc;
% load J
h = 0.2;
cj = 1;
alpha = 0.03;
% T = linspace(120, 200, 100);
% Td = 160;
ft = 1 + ((T -... |
%CALLSIMULATIONANDGRAPHOBJECTS calls the simulation and graphics objects
% into the workspace.
%
% Syntax
% ------
% [sim,gr] = ui.CallSimulationAndGraphObjects();
%
% Details
% -------
% Returns the current simulation and graphics objects, entering them into
% the workspace.
%
% Examples
% --------
% ... |
function foundColorName = ColorName(checkColors)
%checkColors = [38 77 83];
%colorMat = readtable('colortable.csv','Delimiter','@');
%colorMat = table2cell(colorMat);
colorMat = {...
%'Blue', '153.0014 100.2472 125.8768';
'Black', '143.8997 35.5542 53.8000';
'White', '134.8410 41.4204 212.967'...
};
%disp(colorMat);
... |
%script to print out the ENFs
cur_directory = pwd;
training_data_path = 'C:\Users\Andrew\Desktop\Unsorted\UNSW Signal Processing Cup\training_data';
cd(training_data_path);
all_wav = dir('*.wav');
for i = 1:length(all_wav)
[y,fs] = audioread(all_wav(i).name);
[enf1, ~] = extractenf(y,fs,10,2^14,1,9,0.5);
... |
%% Ideal Data
robot.bodyHeight = 0.185;
% robot.bodyHeight = 0.5;
robot.bodyEx = 0.300;
robot.bodyIn = 0.100;
robot.armAngle = deg2rad(10);
% robot.armAngle = 0;
robot.shoulderLength = 0.197;
robot.shoulderLength = 0.6;
robot.shoulderEx = 0.100;
robot.shoulderIn = 0.0900;
robot.elbowHeight = 0.233;
% robot.elbowHeigh... |
function results = uq_lar(Psi, Y, options)
% RESULTS = UQ_LAR(PSI, Y, OPTIONS): sparse regression with Least Angle
% Regression. PSI is the matrix of evaluations of the regressors in the
% experimental design points, while Y are the corresponding model
% responses. The OPTIONS structure is optional and can contai... |
function displayBytes(p)
% PACKET/DISPLAY Displays the packet to the user
%
%It prints all fields as single byte arrays
%in decimal notation
%
%If the DISPAY_HEX global variable is set then it prints in
%hexidecimal notation.
%
%It also prints the number of bytes of each field
%next to it's label in parenthesis.
%
% ... |
function Y = DLM_Inference(x,para)
%input:
% x is the observation sequence, M by N matrix
% para.A, para.T, para.C, para.sigma, para.u0, para.V0 are the model parameters
%output:
% Y.z is the latent state sequence
% Y.P, Y.u, Y.V, Y.K, Y.J, Y.uAll, Y.VAll are the latent parameters
% Y.givenAll is the flag to ind... |
close all
clear all
load('16-07-15v20a-1-10b-15-11pk-11_tr-20_param15V.mat')
%% Currently only focusing on linear run data
%%
str = '16-07-15_v20LinData_TimesIncl';
% Enter particle number here and order parameter
ORDER = 0.95;
% Minimum number of data points (look at FpS?)
MINPOINTS = 100;
q = size(prcle);
% Count is ... |
function Z = cost(X1,alpha, beta, gama, PD , lambda)
Voilation = constraint(X1,PD);
yy = length (X1(:,1));
generation_cost = zeros(yy,1);
for co = 1:yy
generation_cost(co) = generation_cost(co) + sum(alpha + beta.*X1(co,:)+gama.*(X1(co,:).^(2)));
end
Z = generation_cost + lambda .* Voilation;
end
|
function [stiffener_cords,XY_stiffener] = VAT_stiffener_v3_RigidRotational(T01,a,b,stiffener_nodes_number,RigidTheta)
XY_stiffener = zeros(2,stiffener_nodes_number,2);
number_of_nodes = 100001;
x_RHS = linspace(0,a/2,number_of_nodes );
T0 = T01(1)/180*pi;
T1 = T01(2)/180*pi;
if T0 == T1
T1 = T1+1e-2/180*p... |
function [PPInirs] = PPI_nirs(SPM_file, nirs_file, seed_channels, Uu, dir_save,HB)
%SPM_file - name of SPM_indiv_HbX.mat file
%nirs_file - name of filtered, step-removed file
%y is the seed channel time series.
%Uu - Matrix of input variables and contrast weights. This is an
% [n x 3] ... |
%TrainingData_File='csv_data/ACTEWAGL/train_wd.csv';TestingData_File='csv_data/ACTEWAGL/test_wd.csv'; FileName='input_data/ACTEWAGL/elm_input_wd';
%TrainingData_File='csv_data/ACTEWAGL/train_lwd.csv';TestingData_File='csv_data/ACTEWAGL/test_lwd.csv'; FileName='input_data/ACTEWAGL/elm_input_lwd';
%TrainingData_File='csv... |
%% Topological Ordering of Animal Species
%%
set(0, 'DefaultFigurePosition', get(0,'screensize'));
clc; clear; close all;
%% Introduction
% *Units*
% If we were to use RBF units, we would have for every unit an activation:
%
% $$RBF(in, w) = \exp\left( \frac{||in-w||^2}{\sigma} \right)$$
%
% and the winner unit would... |
function [] = demo()
% QMS demo
delete(timerfindall);
mktlogout
clear all; rehash;
% cloud_doc_dir = 'C:\Users\Rick Zhu\Documents\Synology Cloud';
cloud_doc_dir = 'D:';
fn = '\intern\5.ÎâÔÆ·å\optionStraddleTrading\OptInfo.xlsx';
file_path = [cloud_doc_dir, fn];
qms_ = QMS_TEST;
qms_.init(file_path);
pause(30);
vs =... |
function error = errorPosteriori(xActual,xAnterior)
e = abs(xActual-xAnterior);
error = e/xActual;
end
|
function [EEG, HDR] = bdf2eeg(varargin);
% BDF2EEG Reads file in .BDF format and places data in EEGLAB format (EEG struct)
%
% Required inputs: data directory ('pathname')
% filename ('filename')
%
% Optional inputs: re-reference ('reference') DEFAULT= 'none'
% ... |
%sharpening the image by minus the laplacian (second derivative)
function [imgOut]=imsharpen(imgIn,method)
I1=imgIn;
%Preallocate the matrices with zeros
I=zeros(size(imgIn));
%Filter Masks
if method==1
F=[0 1 0; 1 -4 1; 0 1 0];
elseif method==2
F=[1 1 1; 1 -8 1; 1 1 1];
end
%Padarray with zeros
imgIn=padarray(im... |
clear
A = [1 2; 3 5];
b = [4;11];
n = 2;
L=eye(n);
for k = 1:(n-1)
for i= (k+1):n
m = A(i,k)/A(k,k);
A(i,k) = 0;
L(i,k) = m;
for j = (k+1):n
A(i,j) = A(i,j) - m * A(k,j);
endfor;
endfor;
endfor;
y(1) = b(1);
for i = 2:n
soma = 0;
for j = 1:(i-1)
soma = soma + L(i,j) * y(j);
... |
%% This script carries out stall analysis on our aircraft and will output the stall speed
%The stall speed may be determined directly from the wing loading obtained
%at the conceptual poster stage and maximum lift coefficient.
%They will be calculated for take-off, cruise, apprach and landing.
function [Vstall]= ... |
clear all
close all
load('nbModel.mat');
dir_path = '../imageSets/INRIAPerson/Test/pos/';
image = imread(strcat(dir_path,'crop_000006.png'));
tic
[humanBlob, humanMap, blobMeasure] = getHumanBlob(image, nbStruct, model);
toc
%% Output image with human blob
figure
imshow(imfuse(image,humanBlob,'falsecolor','Scaling'... |
layers=[65 65 65];
sae=saesetup(layers);
opts.numepochs = 10;
opts.batchsize = 520;
for i=1:numel(layers)-1
sae.ae{i}.activation_function = 'tanh_opt';
sae.ae{i}.learningRate = 1;
sae.ae{i}.inputZeroMaskedFraction = 0.5;
end
[sae t outx]=saetrain(sae,x,opts);
|
function s = stores(jb,je,ncjt,ndof,nsc,gk)
s = zeros(ndof, ndof);
i = 1;
while i <= 2*ncjt
if i <= ncjt
i1 = (jb - 1)* ncjt + i;
n1 = nsc(i1);
else
i1 = (je - 1)*ncjt + (i - ncjt);
n1 = nsc(i1);
end
if n1 <= ndof
j = 1;
while j <= 2*ncjt
... |
% %
clear
% Test new mediation code
N = 112;
Gr = round(rand(N,1));
Nmed = 1;
V = randn(N,1);
W = randn(N,1);
X = randn(N,Nmed) + 10;
M1 = 0.2*X + randn(N,1)*0.5;% + i;
M2 = 0.2*X + randn(N,1)*0.5;% + i;
Y = 0.3*M1(:,1) + 0*M2(:,1) + 0.5.*X + randn(N,1)*0.5;% + 0.1.*X.*M1(:,1);
% X = randn(N,1);
% M = randn(N,1)... |
%%Recognize Black\White Modules
function [ qr_matrix ] = get_matrix_from_image( image_qr )
image_qr = uint8(ones(size(image_qr)))-uint8(image_qr);
%image_qr = crop_QR(image_qr);
qr_matrix = image_to_matrix(image_qr);
end
%%Crop the image after the right orientation
function [ cropped_image ] = crop_QR(qr)... |
function Pres = PresentationPanelTHR_Geisler
% ---Queries
BeginSPL = paramquery('BeginSPL', 'Begin SPL:', '100', 'dB SPL', ...
'rreal/positive', 'SPL to start recording with.',1);
MaxNPres = paramquery('MaxNPres', 'Max # pres:', '1500', '', ...
'rreal/posint', 'Maximum number of presentations while searching SP... |
function trainnew_Callback(hObject, eventdata, handles)
%% Train a new neural network
cd(handles.data.squeakfolder);
% Apparently, "wind" is a function name, so initialize it as empty
wind = [];
%% Select the tables that contains the training data
waitfor(msgbox('Select Image Tables'))
[trainingdata, trainingpath] = ... |
%% process_input.m
% A script which processes the input string, outputs how many jobs and
% machines there are, as well as providing an initial allocation.
%% Input:
% input_array: n+1 length vector of job costs, and n+1th element is
% # of machines
% init_algo: A string specifying how to pick an init... |
function [ hfig ] = plot_delta_tau( pricer )
%PLOT_DELTA_TAU 画delta~tau的图
% ---------------------
% 沈杰，20160124
% 吴云峰，20160129，增加了不改变原有值的方法
%% 预处理
% TODO: 相关预处理
% 将旧的变量进行保存
original = pricer.getCopy();
%% 作图
tau = 0.01:0.02:0.5;
delta = zeros( 1 , length( tau ) );
for i = 1 : length(tau)
pricer.tau = tau(i);
... |
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