plateform stringclasses 1
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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | NadineKroher/EssentiaProject-master | GetSampleFilesFromMixRef.m | .m | EssentiaProject-master/multiPitch/Matlab/model_learning/GetSampleFilesFromMixRef.m | 1,379 | utf_8 | d98f62c4452157f521e4aa91cbceb8b2 | % Read polyphony and the file names of the samples which compose the
% wavFile (mixture)
% Zhiyao Duan
% 11/14/2008
% Input:
% -wavFile: the wavFile name (including path)
% -samplePath: the path where the samples are stored
% Ouput:
% -Samples: a struct array
% -midinum: the midi number of the s... |
github | brijGit/SPEAKER-RECOGNITION-USING-MFCC-AND-TDA-master | gui_try.m | .m | SPEAKER-RECOGNITION-USING-MFCC-AND-TDA-master/project code/gui_try.m | 4,655 | utf_8 | 039a3a69f0a1cd453c137b32f5fa0c1c | function varargout = gui_try(varargin)
% GUI_TRY M-file for gui_try.fig
% GUI_TRY, by itself, creates a new GUI_TRY or raises the existing
% singleton*.
%
% H = GUI_TRY returns the handle to a new GUI_TRY or the handle to
% the existing singleton*.
%
% GUI_TRY('CALLBACK',hObject,eventData,... |
github | Jrodriguez4/Jaime-Rodriguez-master | Filters.m | .m | Jaime-Rodriguez-master/Projects/Big-Watts/filters_script/Filters.m | 9,764 | utf_8 | c18133dbe29c14ff11e51ef736c7fdc5 | function Filters()
fig=findall(0,'type','figure'); %find all figures
delete(fig); %delete all figures
figure1 = figure('Visible','on','Position', [2000 200 1175 500],'color','white');
%this panle will hold the switch matrix and DUT relevant info.
hLPHP = uipanel('units','pixels','visible','on','Title',...
... |
github | rashikoz/masterThesis-master | trainSvm.m | .m | masterThesis-master/repository/coates/icdar/svm/trainSvm.m | 961 | utf_8 | ae13981251c608d5034c74eddbf26366 | function theta = trainSvm(trainXC, trainY, C)
% setting few options for min func
options.Method = 'lbfgs';
options.maxIter = 1000;
options.display = 'on';
options.TolFun = 1e-5;
options.DerivativeCheck = 'off';
options.MaxFunEvals = 1500;
numClasses = max(trainY);
w0 = zeros(size(trainXC,2)*numClasses, 1);
% based on ... |
github | rashikoz/masterThesis-master | WolfeLineSearch.m | .m | masterThesis-master/repository/coates/icdar/svm/minFunc/minFunc/WolfeLineSearch.m | 10,590 | utf_8 | f962bc5ae0a1e9f80202a9aaab106dab | function [t,f_new,g_new,funEvals,H] = WolfeLineSearch(...
x,t,d,f,g,gtd,c1,c2,LS_interp,LS_multi,maxLS,progTol,debug,doPlot,saveHessianComp,funObj,varargin)
%
% Bracketing Line Search to Satisfy Wolfe Conditions
%
% Inputs:
% x: starting location
% t: initial step size
% d: descent direction
% f: function v... |
github | rashikoz/masterThesis-master | minFunc_processInputOptions.m | .m | masterThesis-master/repository/coates/icdar/svm/minFunc/minFunc/minFunc_processInputOptions.m | 4,103 | utf_8 | 8822581c3541eabe5ce7c7927a57c9ab |
function [verbose,verboseI,debug,doPlot,maxFunEvals,maxIter,optTol,progTol,method,...
corrections,c1,c2,LS_init,cgSolve,qnUpdate,cgUpdate,initialHessType,...
HessianModify,Fref,useComplex,numDiff,LS_saveHessianComp,...
Damped,HvFunc,bbType,cycle,...
HessianIter,outputFcn,useMex,useNegCurv,precFunc... |
github | rashikoz/masterThesis-master | trainSvm.m | .m | masterThesis-master/repository/rusinol/icdar/svm/trainSvm.m | 961 | utf_8 | ae13981251c608d5034c74eddbf26366 | function theta = trainSvm(trainXC, trainY, C)
% setting few options for min func
options.Method = 'lbfgs';
options.maxIter = 1000;
options.display = 'on';
options.TolFun = 1e-5;
options.DerivativeCheck = 'off';
options.MaxFunEvals = 1500;
numClasses = max(trainY);
w0 = zeros(size(trainXC,2)*numClasses, 1);
% based on ... |
github | rashikoz/masterThesis-master | WolfeLineSearch.m | .m | masterThesis-master/repository/rusinol/icdar/svm/minFunc/minFunc/WolfeLineSearch.m | 10,590 | utf_8 | f962bc5ae0a1e9f80202a9aaab106dab | function [t,f_new,g_new,funEvals,H] = WolfeLineSearch(...
x,t,d,f,g,gtd,c1,c2,LS_interp,LS_multi,maxLS,progTol,debug,doPlot,saveHessianComp,funObj,varargin)
%
% Bracketing Line Search to Satisfy Wolfe Conditions
%
% Inputs:
% x: starting location
% t: initial step size
% d: descent direction
% f: function v... |
github | rashikoz/masterThesis-master | minFunc_processInputOptions.m | .m | masterThesis-master/repository/rusinol/icdar/svm/minFunc/minFunc/minFunc_processInputOptions.m | 4,103 | utf_8 | 8822581c3541eabe5ce7c7927a57c9ab |
function [verbose,verboseI,debug,doPlot,maxFunEvals,maxIter,optTol,progTol,method,...
corrections,c1,c2,LS_init,cgSolve,qnUpdate,cgUpdate,initialHessType,...
HessianModify,Fref,useComplex,numDiff,LS_saveHessianComp,...
Damped,HvFunc,bbType,cycle,...
HessianIter,outputFcn,useMex,useNegCurv,precFunc... |
github | suriyadeepan/frhp-wsn-master | FtspDataAnalyzer.m | .m | frhp-wsn-master/basestation/FtspDataAnalyzer.m | 1,814 | utf_8 | b5321ca4514924c4534deb7594a32166 | %load file written out by FtspDataLogger.java class
%arg0 - filename, e.g. '1205543689171.report'
function FTSPDataAnalyzer(file, varargin)
[c1 c2 c3 c4 c5]= textread(file, '%u %u %u %u %u', 'commentstyle', 'shell');
data = [c2 c3 c4 c5]; %skipping the first column (java time)
data1 = sortrows(sortrows(data,1),2);... |
github | suriyadeepan/frhp-wsn-master | FtspDataAnalyzer.m | .m | frhp-wsn-master/relay/FtspDataAnalyzer.m | 1,814 | utf_8 | b5321ca4514924c4534deb7594a32166 | %load file written out by FtspDataLogger.java class
%arg0 - filename, e.g. '1205543689171.report'
function FTSPDataAnalyzer(file, varargin)
[c1 c2 c3 c4 c5]= textread(file, '%u %u %u %u %u', 'commentstyle', 'shell');
data = [c2 c3 c4 c5]; %skipping the first column (java time)
data1 = sortrows(sortrows(data,1),2);... |
github | suriyadeepan/frhp-wsn-master | FtspDataAnalyzer.m | .m | frhp-wsn-master/source/FtspDataAnalyzer.m | 1,814 | utf_8 | b5321ca4514924c4534deb7594a32166 | %load file written out by FtspDataLogger.java class
%arg0 - filename, e.g. '1205543689171.report'
function FTSPDataAnalyzer(file, varargin)
[c1 c2 c3 c4 c5]= textread(file, '%u %u %u %u %u', 'commentstyle', 'shell');
data = [c2 c3 c4 c5]; %skipping the first column (java time)
data1 = sortrows(sortrows(data,1),2);... |
github | aschneer/algorithmic_trading_simulation-master | StockQuoteQuery.m | .m | algorithmic_trading_simulation-master/code/sqq/StockQuoteQuery.m | 9,456 | utf_8 | 42aa00600d74e57c301ef53611c0c149 | function [date, close, open, low, high, volume, closeadj] = StockQuoteQuery(symbol, start_date, end_date, frequency, varargin)
% STOCKQUOTEQUERY -- Fetch historical stock prices for a given ticker symbol
% from the YAHOO web serve using the MATLAB Java URL interface.
% See SQQ for a function that calls STO... |
github | APMonitor/apm_matlab-master | cstr1.m | .m | apm_matlab-master/example_cstr_seq/cstr1.m | 1,334 | utf_8 | 011b27458c3d159f2ed713bd3963cfec | % This model is used for comparison with ode15s
% It isn't used by the APM code
% CSTR model from
%
% Michael A. Henson and Dale E. Seborg. Nonlinear Process Control.
% Prentice Hall PTR, Upper Saddle River, New Jersey, 1997.
% Description:
% Continuously Stirred Tank Reactor with energy balance and reaction A-... |
github | APMonitor/apm_matlab-master | apm_solve.m | .m | apm_matlab-master/apm/apm_solve.m | 3,490 | utf_8 | bcce9d3a1993c459352c255c46bd5f49 | % APM Solver for simulation, estimation, and optimization with both
% static (steady-state) and dynamic models. The dynamic modes can solve
% index 2+ DAEs without numerical differentiation.
%
% y = apm_solve(app,imode)
%
% Function apm_solve uploads the model file (apm) and optionally
% a data file (csv) with the... |
github | APMonitor/apm_matlab-master | apm_web.m | .m | apm_matlab-master/apm/apm_web.m | 866 | utf_8 | 7d1895a1f6af8f2fc305e0f725f54f9d | % APM Open Web Viewer in Internet Browser
%
% stat = apm_web(server,app)
%
% Function apm_web opens the default web-browser
% and loads the application in dashboard view
% with the following arguments:
%
% server = address of server
% app = application name
% stat = message returned when opening browser
... |
github | APMonitor/apm_matlab-master | apm_details.m | .m | apm_matlab-master/apm/apm_details.m | 4,624 | utf_8 | 2ef4a1844a962881fdb040e0a96042e0 | % APM Report Problem Details
%
% y = apm_details(server,app,x,lam)
%
% This function reports the details of a problem
% located on the APM server with the following arguments:
%
% server = address of server
% app = application name
% x = values of all variables
% lam = Lagrange multipliers
% ... |
github | APMonitor/apm_matlab-master | apm_meas.m | .m | apm_matlab-master/apm/apm_meas.m | 757 | utf_8 | 5f771377d1c92a378e848aa72e583fac | % APM Input Measured Value
%
% response = apm_meas(server,app,name,value)
%
% Function apm_meas sends a measurement to the APM server
% with the following arguments:
%
% server = address of server
% app = application name
% name = parameter or variable name
% value = measurement value
%
% A response is ... |
github | APMonitor/apm_matlab-master | apm_app.m | .m | apm_matlab-master/apm/apm_app.m | 1,007 | utf_8 | 7a7f3b02f3e9c6138d48921d3357868d | % APM Load Application
%
% app = apm_app(server,name)
%
% Function apm_app loads a model file (apm) and optionally
% a data file (csv) to the APM server with the
% following arguments:
%
% app = application name
% server = address of server
% name = loads name.apm and name.csv
%
function [app] = apm_ap... |
github | APMonitor/apm_matlab-master | apm_option.m | .m | apm_matlab-master/apm/apm_option.m | 960 | utf_8 | 279bcbb0829b4a371c623eaf5e8b485d | % APM Specify Options
%
% response = apm_option(server,app,name,value)
%
% Function apm_option sends an option specification
% to the APM server with the following arguments:
%
% server = address of server
% app = application name
% name = option name
% value = option value
%
% A response is returned i... |
github | APMonitor/apm_matlab-master | apm_sol.m | .m | apm_matlab-master/apm/apm_sol.m | 2,094 | utf_8 | ec1ac2f1d20a675fc58cabb61d89c6f3 | % APM Retrieve Solution in Structure Format
%
% y = apm_sol(server,app)
%
% Function apm_sol retrieves the solution from the APM server
% with the following arguments:
%
% Input: server = server web-address to retrieve the solution
% app = application name
%
% Output: y.names = names of all variables... |
github | APMonitor/apm_matlab-master | apm_get.m | .m | apm_matlab-master/apm/apm_get.m | 743 | utf_8 | 49d4f0fa76dc39327ef761032bc4733d | % APM Retrieve File From Server
%
% [] = apm_get(server,app,filename)
%
% Function apm_get retrieves the file from the web-server
% with the following arguments:
%
% server = address of server
% app = application name
% filename = filename to retrieve
%
% A list of all file names that are accessible can be
% ... |
github | APMonitor/apm_matlab-master | csv_element.m | .m | apm_matlab-master/apm/csv_element.m | 490 | utf_8 | 88e19c935df98c1bf2e54eef60862209 | % Retrieve CSV element
%
% value = csv_element(name,row,csv)
%
% This function looks up "name" in the cell
% array "csv" and returns the value in row
% number "row"
%
function value = csv_element(name,row,csv)
% Size of CSV data
[rows,cols] = size(csv);
% Take last row if beyond max rows
if (row>rows),
... |
github | APMonitor/apm_matlab-master | apm_info.m | .m | apm_matlab-master/apm/apm_info.m | 515 | utf_8 | 432933c13af1202ae555fa33eddc0f61 | % APM Variable Classification
% class = FV, MV, SV, CV
% F or FV = Fixed value - parameter may change to a new value every cycle
% M or MV = Manipulated variable - independent variable over time horizon
% S or SV = State variable - model variable for viewing
% C or CV = Controlled variable - model variable for ... |
github | APMonitor/apm_matlab-master | apm_web_var.m | .m | apm_matlab-master/apm/apm_web_var.m | 815 | utf_8 | c934507e28efe9eb756884e39718c275 | % APM Open Web Page with Variable Values
%
% stat = apm_web_var(server,app)
%
% Function apm_web_var opens the default web-browser
% and loads a table of variable values
%
% server = address of server
% app = application name
% stat = message returned when opening browser
%
function [stat] = apm_web_var(... |
github | APMonitor/apm_matlab-master | apm_id.m | .m | apm_matlab-master/apm/apm_id.m | 6,281 | utf_8 | dca43bc0ff7e72ea4e3dc8a94c86778e | % Function apm_id for identification of a linear model
% Inputs
% data = data set with time, inputs, outputs
% ni = number of inputs (others are outputs)
% nu = number of input terms (numerator)
% ny = number of output terms (denominator)
%
% Outputs
% sysd = discrete transfer function estimated from ... |
github | APMonitor/apm_matlab-master | csv_data.m | .m | apm_matlab-master/apm/csv_data.m | 613 | utf_8 | 2f0e599738b96e8e379066559fd6b1a5 | % Load CSV File into MATLAB
%
% A = csv_data(filename)
%
% Function csv_data extracts data from a comma
% separated value (csv) file and returns it
% to the matrix A
%
function [A] = csv_data(filename)
% load data from csv file with header
fid = fopen(filename, 'r');
aline = fgetl(fid);
% Split hea... |
github | APMonitor/apm_matlab-master | parse.m | .m | apm_matlab-master/apm/parse.m | 371 | utf_8 | a56510df99a8fdb7fb06fd8841112096 | % Parse line with delimiter "delim" and return
% the delimited pieces in the reponse "parts"
function parts = parse(str,delim)
splitlen = length(delim);
parts = {};
while 1
k = strfind(str, delim);
if isempty(k)
parts{end+1} = str;
break
end
parts{end+1} = str(1 : k(... |
github | APMonitor/apm_matlab-master | apm_load.m | .m | apm_matlab-master/apm/apm_load.m | 1,034 | utf_8 | 187f6e4d81da611fce4277b7406ed265 | % APM Load Model File
%
% response = apm_load(server,app,filename)
%
% Function apm_load uploads the model file (apm) to the web-server
% with the following arguments:
%
% server = address of server
% app = application name
% filename = model filename
%
% A response is returned indicating whether the file was ... |
github | APMonitor/apm_matlab-master | apm.m | .m | apm_matlab-master/apm/apm.m | 1,230 | utf_8 | c71a58564ab0c1f50777e776fa996688 | % APM Web-Interface Command
%
% response = apm(server,app,command)
%
% This function sends a command to the APM server with
% the following arguments:
%
% server = address of server
% app = application name
% command = instruction or line sent
%
% Some commands are:
% solve : solve the model on the ser... |
github | APMonitor/apm_matlab-master | csv_lookup.m | .m | apm_matlab-master/apm/csv_lookup.m | 385 | utf_8 | f9ba7425f621634184b2a702390ce7db | % Retrieve CSV element by finding the
% matching name in the csv data
function result = csv_lookup(name,csv)
% Initialize value
result = 0;
% Size of CSV data
[rows,cols] = size(csv);
% Find matching name column in csv data
match = strcmpi(deblank(name),csv(1,:));
% Retrieve value
for i = 1:... |
github | APMonitor/apm_matlab-master | csv_load.m | .m | apm_matlab-master/apm/csv_load.m | 1,152 | utf_8 | a24da988dc8bf52a854d63064b70e1b5 | % APM Load Data File
%
% response = csv_load(server,app,filename)
%
% Function csv_load uploads the data file (csv) to the web-server
% with the following arguments:
%
% server = address of server
% app = application name
% filename = data filename
%
% A response is returned indicating whether the file was
% ... |
github | APMonitor/apm_matlab-master | apm_web_root.m | .m | apm_matlab-master/apm/apm_web_root.m | 685 | utf_8 | c6e6de38444d891fbd8e29b7426278f7 | % APM Open Web Root Folder in Internet Browser
%
% stat = apm_web_root(server,app)
%
% Function apm_web_root opens the default web-browser
% and loads a list of files that can be selected for
% download or viewing
%
% server = address of server
% app = application name
% stat = message returned when open... |
github | APMonitor/apm_matlab-master | apm_tag.m | .m | apm_matlab-master/apm/apm_tag.m | 1,049 | utf_8 | 920a1364243a3b9f5319297d1b330ead | % APM Retrieve an Option Value (Tag)
%
% response = apm_tag(server,app,name)
%
% Function apm_tag retrieves an option specification from
% the APM server with the following arguments:
%
% server = address of server
% app = application name
% name = option name
% response = option value
%
% Either global op... |
github | APMonitor/apm_matlab-master | t0_load.m | .m | apm_matlab-master/apm/t0_load.m | 1,608 | utf_8 | eb54476fb0fcdf48bbce9f137ca0c98f | % APM Load T0 File
% File is typically either:
% Steady State with ss.t0, mpu.t0, rto.t0,
% Dynamic with sim.t0, est.t0, ctl.t0,
% Sequential with sqs.t0
% Warmstart with warm.t0
% Lagrange mult with lam.t0
function [response] = t0_load(server,app,filename)
% extract mode by removing .t0
... |
github | APMonitor/apm_matlab-master | cstr1.m | .m | apm_matlab-master/example_cstr_steps/cstr1.m | 1,334 | utf_8 | 011b27458c3d159f2ed713bd3963cfec | % This model is used for comparison with ode15s
% It isn't used by the APM code
% CSTR model from
%
% Michael A. Henson and Dale E. Seborg. Nonlinear Process Control.
% Prentice Hall PTR, Upper Saddle River, New Jersey, 1997.
% Description:
% Continuously Stirred Tank Reactor with energy balance and reaction A-... |
github | APMonitor/apm_matlab-master | cstr1.m | .m | apm_matlab-master/example_cstr_simul/cstr1.m | 1,334 | utf_8 | 011b27458c3d159f2ed713bd3963cfec | % This model is used for comparison with ode15s
% It isn't used by the APM code
% CSTR model from
%
% Michael A. Henson and Dale E. Seborg. Nonlinear Process Control.
% Prentice Hall PTR, Upper Saddle River, New Jersey, 1997.
% Description:
% Continuously Stirred Tank Reactor with energy balance and reaction A-... |
github | qingxiang-jia/gesture_recognizer-master | iterExample.m | .m | gesture_recognizer-master/iterExample.m | 135 | utf_8 | d2ace824741c544288a0ea99da128542 | % iterating through a cell array
function [] = iter(cellArray)
for i = 1:size(cellArray, 2)
disp(cellArray{i});
end
end |
github | qingxiang-jia/gesture_recognizer-master | LineCurvature2D.m | .m | gesture_recognizer-master/LineCurvature2D.m | 4,176 | utf_8 | 89ee0a2a99bea815784b23a07aaed325 | function k=LineCurvature2D(Vertices,Lines)
% This function calculates the curvature of a 2D line. It first fits
% polygons to the points. Then calculates the analytical curvature from
% the polygons;
%
% k = LineCurvature2D(Vertices,Lines)
%
% inputs,
% Vertices : A M x 2 list of line points.
% (optiona... |
github | qingxiang-jia/gesture_recognizer-master | recognizeGesture.m | .m | gesture_recognizer-master/recognizeGesture.m | 1,022 | utf_8 | e07cc714d8ece31c7c94dd5c8855c0b2 | % take an image file and return the recognized gestures
function [gesture, location] = recognizeGesture(fileName) % fileName: the image file
img = imread(fileName); % read in the file, must be in the same directory
gestureImg = im2bw(imresize(img, 4160/size(img, 2)*0.1), 0.5); % reduce to binary, "4160" part just make ... |
github | qingxiang-jia/gesture_recognizer-master | skinDetect2Func.m | .m | gesture_recognizer-master/skinDetect2Func.m | 1,153 | utf_8 | 2bfe464b4d7f1c8716cb5dc2e84adcb3 | %skin detect return pixels
function out=skinDetect2func(img)
imshow(img);
sz=size(img);
r=1;g=2;b=3;y=1;u=2;v=3;
yuv=img;
region=yuv;
for i=1:sz(1)
for j=1:sz(2)
yuv(i,j,y)=(img(i,j,r)+2*img(i,j,g)+img(i,j,b))/4;
yuv(i,j,u)=img(i,j,r)-img(i,j,g);
yuv(i,j,v)=img(i,j,b)-img(i,j,... |
github | qingxiang-jia/gesture_recognizer-master | detectWhere.m | .m | gesture_recognizer-master/detectWhere.m | 594 | utf_8 | d939f1636f5055762f7d6526f2366c14 | % detect where the given gesture is on the screen
function location = detectWhere( sample, template )
%DETECTOR useless
% sample=reduced sample gray image
% template=reduced binary image
% x, y represent the center of the template found
% likelihood=how likely it is template
c = normxcorr2(template,sample);
[ypeak, xp... |
github | qingxiang-jia/gesture_recognizer-master | iterExample.m | .m | gesture_recognizer-master/helper_files/iterExample.m | 135 | utf_8 | d2ace824741c544288a0ea99da128542 | % iterating through a cell array
function [] = iter(cellArray)
for i = 1:size(cellArray, 2)
disp(cellArray{i});
end
end |
github | qingxiang-jia/gesture_recognizer-master | detectWhere.m | .m | gesture_recognizer-master/helper_files/detectWhere.m | 594 | utf_8 | d939f1636f5055762f7d6526f2366c14 | % detect where the given gesture is on the screen
function location = detectWhere( sample, template )
%DETECTOR useless
% sample=reduced sample gray image
% template=reduced binary image
% x, y represent the center of the template found
% likelihood=how likely it is template
c = normxcorr2(template,sample);
[ypeak, xp... |
github | qingxiang-jia/gesture_recognizer-master | LineCurvature2D.m | .m | gesture_recognizer-master/useless/LineCurvature2D.m | 4,176 | utf_8 | 89ee0a2a99bea815784b23a07aaed325 | function k=LineCurvature2D(Vertices,Lines)
% This function calculates the curvature of a 2D line. It first fits
% polygons to the points. Then calculates the analytical curvature from
% the polygons;
%
% k = LineCurvature2D(Vertices,Lines)
%
% inputs,
% Vertices : A M x 2 list of line points.
% (optiona... |
github | icopavan/PULocalization-master | getCU_Status.m | .m | PULocalization-master/getCU_Status.m | 999 | utf_8 | 6e82d02f15c96ef78c0302af9560fede | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getMaxLevelSectorNum.m | .m | PULocalization-master/getMaxLevelSectorNum.m | 791 | utf_8 | 962007a21e971687ae800138e490ca83 | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getSector.m | .m | PULocalization-master/getSector.m | 1,343 | utf_8 | 3df252bc9737fecea47bcefed8c13ea2 | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getDisableSectorIDs.m | .m | PULocalization-master/getDisableSectorIDs.m | 2,014 | utf_8 | 4be3865604929129793d5493a0aa4bea | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | run.m | .m | PULocalization-master/run.m | 1,949 | utf_8 | 7cdee75883fdec39eaf91a221fa15392 | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getDisableLevelIDs.m | .m | PULocalization-master/getDisableLevelIDs.m | 1,091 | utf_8 | 9eab725acee215899c5777aa0e9f33fb | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getCU_Status_Gom.m | .m | PULocalization-master/getCU_Status_Gom.m | 733 | utf_8 | cb35e36619077f1d63fef31fc2941332 | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | main.m | .m | PULocalization-master/main.m | 6,044 | utf_8 | 2c8fe4561ed374e3647ddc6b693fb82d | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | icopavan/PULocalization-master | getLevel.m | .m | PULocalization-master/getLevel.m | 798 | utf_8 | cdfd563dca7036f9794992af6fe9b1c0 | %%Code written by Deepti Singhal from IIIT, Hyderabad.
%Publication for citation: [Singhal, D.; Sharma, M.K.; Garimella, R.M.,
%"Energy efficient localization of primary users for avoiding interference
%in cognitive networks," Computer Communication and Informatics (ICCCI),
%2012 International Conference on , vol., no.... |
github | createwindow/pjsip-blf-master | echo_diagnostic.m | .m | pjsip-blf-master/third_party/speex/libspeex/echo_diagnostic.m | 2,076 | utf_8 | 8d5e7563976fbd9bd2eda26711f7d8dc | % Attempts to diagnose AEC problems from recorded samples
%
% out = echo_diagnostic(rec_file, play_file, out_file, tail_length)
%
% Computes the full matrix inversion to cancel echo from the
% recording 'rec_file' using the far end signal 'play_file' using
% a filter length of 'tail_length'. The output is saved to 'o... |
github | michael0113/KinectSimulator-master | read_obj.m | .m | KinectSimulator-master/opcodemesh/matlab/read_obj.m | 13,890 | utf_8 | c2c4b6ba2cde8584bb5af7d340db08cd | function OBJ=read_wobj(fullfilename)
% Read the objects from a Wavefront OBJ file
%
% OBJ=read_wobj(filename);
%
% OBJ struct containing:
%
% OBJ.vertices : Vertices coordinates
% OBJ.vertices_texture: Texture coordinates
% OBJ.vertices_normal : Normal vectors
% OBJ.vertices_point : Vertice data used for points and li... |
github | biogeochemistry/MyLake_public-master | hfbulktc.m | .m | MyLake_public-master/v12/air_sea/hfbulktc.m | 11,872 | utf_8 | 1d91f1bf21ae955f8b71a23de600fd35 | function A=hfbulktc(ur,zr,Ta,zt,rh,zq,Pa,Ts,sal,dlw,dsw,nsw)
% HFBULKTC: computes sensible and latent heat fluxes and other variables.
% A=HFBULKTC(ur,zr,Ta,zt,rh,zq,Pa,Ts,sal,dlw,dsw,nsw) computes the following:
%
% Hs = sensible heat flux INTO ocean [W/m^2]
% Hl = latent heat flux INTO ocean... |
github | biogeochemistry/MyLake_public-master | cool_skin.m | .m | MyLake_public-master/v12/air_sea/cool_skin.m | 7,518 | utf_8 | c498431a06857156738bb02881093d6b | function [delta,Dter,Dqer] = cool_skin(sal,Tw,rhoa,cpa,Pa, ...
U_star,T_star,Q_star, ...
dlw,dsw,nsw,delta,g,Rgas, ...
CtoK,Qsat_coeff)
% COOL_SKIN: compute the cool-skin parameters.
% COOL_... |
github | biogeochemistry/MyLake_public-master | hfbulktc_speed.m | .m | MyLake_public-master/v12/air_sea/hfbulktc_speed.m | 12,241 | utf_8 | c5291c2e729e98406d394fc721cc7bad | % As hfbulktc.m but in order to speed up the function, the iteration loop is
% changed from "if" to "while" structure by TSA 05.09.03
function A=hfbulktc_speed(ur,zr,Ta,zt,rh,zq,Pa,Ts,sal,dlw,dsw,nsw)
% HFBULKTC: computes sensible and latent heat fluxes and other variables.
% A=HFBULKTC(ur,zr,Ta,zt,rh,zq,Pa,Ts,sal,dl... |
github | biogeochemistry/MyLake_public-master | reedcf.m | .m | MyLake_public-master/v12/air_sea/reedcf.m | 3,943 | utf_8 | a868371ec818451f13265398804019c4 | function c = reedcf(yd,lat,dsw);
% REEDCF: computes daily mean cloud cover following Reed (1977).
% c = REEDCF(yd,lat,dsw) computes daily averaged cloud cover c from
% yearday, latitude, and measured insolation following Reed (1977), J. Phys.
% Oceanog., 7, 482-485. Assumes hourly input series are either both ... |
github | biogeochemistry/MyLake_public-master | modelinputs_v12.m | .m | MyLake_public-master/v12/v12/modelinputs_v12.m | 6,636 | utf_8 | b4303c933168b88d98c54eebed5745f1 | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2005
%
% Module for reading input data and parameters
% Code checked by TSA, xx.03.2005
% Last modified by TSA, 15.08.2006 (Az replaced by In_Az 10.03.06; Possibility to have NaN in Global rad. series, 15.08.06)
function ... |
github | biogeochemistry/MyLake_public-master | IOflow_v11.m | .m | MyLake_public-master/v12/v12/IOflow_v11.m | 1,795 | utf_8 | 91dc34786335f94ea76e649e608da18e | % === MyLake model, version 1.1, 16.03.04 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2004
%
% Module for calculating river inflow and its effect on profiles of temperature and other state variables
% Code checked by TSA, 16.3.2004
% INPUTS:
% vertical arrays: z is model grid, Vz is layer volume, Tz layer prop... |
github | biogeochemistry/MyLake_public-master | heatflux_v12.m | .m | MyLake_public-master/v12/v12/heatflux_v12.m | 3,866 | utf_8 | c2ac59002c564b594507ca488a499d58 | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2005
%
% Module for calculating heat fluxes and other physical parameters
% Code checked by TSA, 03.03.2005
% Last modified by TSA, 03.03.2005
function [Qsw,Qlw,Qsl,tau,Dayfrac,Dayfracheating] = heatflux_v12(t,GR,CC,Ta,Ra,P... |
github | biogeochemistry/MyLake_public-master | solvemodel_v12.m | .m | MyLake_public-master/v12/v12/solvemodel_v12.m | 51,145 | utf_8 | f7683c3e126951451f64b60c200425e3 | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2005
%
% Main module
% Code checked by TSA, xx.03.2005
% Last modified by TSA, 15.08.2006 (temperature profile sent to convection.m, Thermocline-bug corrected)
function [zz,Az,Vz,tt,Qst,Kzt,Tzt,Czt,Szt,Pzt,Chlzt,PPzt,DOPzt,DOCzt,Q... |
github | biogeochemistry/MyLake_public-master | sedimentheat_v11.m | .m | MyLake_public-master/v12/v12/sedimentheat_v11.m | 929 | utf_8 | 14ee5f9a51fc53d7f38e7babf43d624e | % === MyLake model, version 1.1, 16.03.04 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2004
%
% Module for calculating new temperature profile in sediments
% Code checked by TSA, 16.03.2004
function [Tzy_sed_updated] = sedimentheat_v11(Tzy_sed, K_sed, dt)
% Grid resolution in sediment is 0.2 m in the 0-2 layer and 0... |
github | biogeochemistry/MyLake_public-master | convection_v12_1a.m | .m | MyLake_public-master/v12/v12/convection_v12_1a.m | 4,375 | utf_8 | 5cf9184d7b46888e8350373d5f0daf7a | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2004
% VERSION 1.2.1a, based on convection_v12 (with three modified lines of code, marked with NEW!!!)
% Convection module
% Code checked by TSA, 07.03.05
% Last modified by TSA, 17.07.07
function [Tz,Cz,Sz,Pz,Chlz,PPz,DOPz,DOCz]... |
github | biogeochemistry/MyLake_public-master | convection_v12_1a.m | .m | MyLake_public-master/v12/v12_1/convection_v12_1a.m | 4,375 | utf_8 | 5cf9184d7b46888e8350373d5f0daf7a | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2004
% VERSION 1.2.1a, based on convection_v12 (with three modified lines of code, marked with NEW!!!)
% Convection module
% Code checked by TSA, 07.03.05
% Last modified by TSA, 17.07.07
function [Tz,Cz,Sz,Pz,Chlz,PPz,DOPz,DOCz]... |
github | biogeochemistry/MyLake_public-master | solvemodel_v12_1b_ut.m | .m | MyLake_public-master/v12/v12_1/solvemodel_v12_1b_ut.m | 55,531 | utf_8 | 293610e34d4870bb36299767d575857f | % === MyLake model, version 1.2, 15.03.05 ===
% by Tom Andersen & Tuomo Saloranta, NIVA 2005
%
% VERSION 1.2.1 (two phytoplankton groups are included; variable Cz denotes
% this second group now. Frazil ice included + some small bug-fixes and code rearrangements. Using convection_v12_1a.m code)
%
% Main module
% Code c... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | jdqr.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/jdqr.m | 73,068 | utf_8 | b45810ddb5b2767c9289909175d1dc04 | function varargout=jdqr(varargin)
%JDQR computes a partial Schur decomposition of a square matrix or operator.
% Lambda = JDQR(A) returns the absolute largest eigenvalues in a K vector
% Lambda. Here K=min(5,N) (unless K has been specified), where N=size(A,1).
% JDQR(A) (without output argument) displays the K eige... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | lmnn.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/lmnn.m | 5,421 | utf_8 | 8d5b80dee8cf8730a96c0c415c5876fc | function [M, L, Y, C] = lmnn(X, labels)
%LMNN Learns a metric using large-margin nearest neighbor metric learning
%
% [M, L, Y, C] = lmnn(X, labels)
%
% The function uses large-margin nearest neighbor (LMNN) metric learning to
% learn a metric on the data set specified by the NxD matrix X and the
% corresponding Nx1 ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | d2p.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/d2p.m | 3,487 | utf_8 | 0c7024a8039ea16b937d283585883fc3 | function [P, beta] = d2p(D, u, tol)
%D2P Identifies appropriate sigma's to get kk NNs up to some tolerance
%
% [P, beta] = d2p(D, kk, tol)
%
% Identifies the required precision (= 1 / variance^2) to obtain a Gaussian
% kernel with a certain uncertainty for every datapoint. The desired
% uncertainty can be specified... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | cg_update.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/cg_update.m | 3,715 | utf_8 | 1556078ae7c31950ec738949384cf180 | % Version 1.000
%
% Code provided by Ruslan Salakhutdinov and Geoff Hinton
%
% Permission is granted for anyone to copy, use, modify, or distribute this
% program and accompanying programs and documents for any purpose, provided
% this copyright notice is retained and prominently displayed, along with
% a note saying t... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | lmvu.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/lmvu.m | 8,540 | utf_8 | c8003ed7ff0fd0e226776c42c72ad385 | function [mappedX, mapping] = lmvu(X, no_dims, K, LL)
%LMVU Performs Landmark MVU on dataset X
%
% [mappedX, mapping] = lmvu(X, no_dims, k1, k2)
%
% The function performs Landmark MVU on the DxN dataset X. The value of k1
% represents the number of nearest neighbors that is employed in the MVU
% constraints. The val... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | cca.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/cca.m | 14,846 | utf_8 | 935e971ffe825a64e0eb80c535d71ebb | function [Z, ccaEigen, ccaDetails] = cca(X, Y, EDGES, OPTS)
%
% Function [Z, CCAEIGEN, CCADETAILS] = CCA(X, Y, EDGES, OPTS) computes a low
% dimensional embedding Z in R^d that maximally preserves angles among input
% data X that lives in R^D, with the algorithm Conformal Component Analysis.
%
% The embedding Z is co... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | x2p.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/x2p.m | 3,597 | utf_8 | 4a102e94922f4af38e36c374dccbc5a2 | function [P, beta] = x2p(X, u, tol)
%X2P Identifies appropriate sigma's to get kk NNs up to some tolerance
%
% [P, beta] = x2p(xx, kk, tol)
%
% Identifies the required precision (= 1 / variance^2) to obtain a Gaussian
% kernel with a certain uncertainty for every datapoint. The desired
% uncertainty can be specifie... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | sammon.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/sammon.m | 7,108 | utf_8 | 8a1fccbea9525bbebae4039127005ea6 | function [y, E] = sammon(x, n, opts)
%SAMMON Performs Sammon's MDS mapping on dataset X
%
% Y = SAMMON(X) applies Sammon's nonlinear mapping procedure on
% multivariate data X, where each row represents a pattern and each column
% represents a feature. On completion, Y contains the corresponding
% co-ordin... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | sdecca2.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/sdecca2.m | 7,185 | utf_8 | e53979561adda6a23883da0e72af5bf6 | function [P, newY, L, newV, idx]= sdecca2(Y, snn, regularizer, relative)
% doing semidefinitve embedding/MVU with output being parameterized by graph
% laplacian's eigenfunctions..
%
% the algorithm is same as conformal component analysis except that the scaling
% factor there is set as 1
%
%
% function [P, newY, Y] ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | sparse_nn.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/sparse_nn.m | 972 | utf_8 | df5da172f954ec2f53125a04787cf2d3 | %SPARSE_NN
%
% This file is part of the Matlab Toolbox for Dimensionality Reduction.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | jdqz.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/techniques/jdqz.m | 78,986 | utf_8 | be67a038982588a6ac9cbc2d36f009e8 | function varargout=jdqz(varargin)
%JDQZ computes a partial generalized Schur decomposition (or QZ
% decomposition) of a pair of square matrices or operators.
%
% LAMBDA=JDQZ(A,B) and JDQZ(A,B) return K eigenvalues of the matrix pair
% (A,B), where K=min(5,N) and N=size(A,1) if K has not been specified.
%
% [X,J... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | lnst.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/lnst.m | 866 | utf_8 | fd307c356d0eb128b0d57c9df000197e | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of the or... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | scatter12n.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/scatter12n.m | 1,309 | utf_8 | 5a079c0bf3db6d26fd87f0cb3297c45b | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of the or... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | not_calculated.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/not_calculated.m | 7,602 | utf_8 | 9f98d51f0c8207bd788383e580814903 | function varargout = not_calculated(varargin)
% NOT_CALCULATED M-file for not_calculated.fig
% NOT_CALCULATED by itself, creates a new NOT_CALCULATED or raises the
% existing singleton*.
%
% H = NOT_CALCULATED returns the handle to a new NOT_CALCULATED or the handle to
% the existing singleton*.
%
%... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | choose_method.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/choose_method.m | 5,336 | utf_8 | a50c15d7c51725e6e88bb12bf5be57a3 | function varargout = choose_method(varargin)
% CHOOSE_METHOD M-file for choose_method.fig
% CHOOSE_METHOD, by itself, creates a new CHOOSE_METHOD or raises the existing
% singleton*.
%
% H = CHOOSE_METHOD returns the handle to a new CHOOSE_METHOD or the handle to
% the existing singleton*.
%
% ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | load_data_1_var.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/load_data_1_var.m | 4,776 | utf_8 | 213540e0f2d0e24db85ee4c6184178c8 | function varargout = load_data_1_var(varargin)
% LOAD_DATA_1_VAR M-file for load_data_1_var.fig
% LOAD_DATA_1_VAR, by itself, creates a new LOAD_DATA_1_VAR or raises the existing
% singleton*.
%
% H = LOAD_DATA_1_VAR returns the handle to a new LOAD_DATA_1_VAR or the handle to
% the existing singlet... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | plotn.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/plotn.m | 3,947 | utf_8 | ba3674531d91bc0b2ca405e0a9d0bc3a | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of the or... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | scattern.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/scattern.m | 3,514 | utf_8 | aca2d60a4f80079c67204845b2499143 | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of the or... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | no_history.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/no_history.m | 7,508 | utf_8 | d5c85b897eeca97b3e37ea41551de2b1 | function varargout = no_history(varargin)
% NO_HISTORY M-file for no_history.fig
% NO_HISTORY by itself, creates a new NO_HISTORY or raises the
% existing singleton*.
%
% H = NO_HISTORY returns the handle to a new NO_HISTORY or the handle to
% the existing singleton*.
%
% NO_HISTORY('CALLBACK',... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | load_data_vars.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/load_data_vars.m | 7,727 | utf_8 | a89e86bdd4785b42127825a4c304fb5e | function varargout = load_data_vars(varargin)
% LOAD_DATA_VARS M-file for load_data_vars.fig
% LOAD_DATA_VARS, by itself, creates a new LOAD_DATA_VARS or raises the existing
% singleton*.
%
% H = LOAD_DATA_VARS returns the handle to a new LOAD_DATA_VARS or the handle to
% the existing singleton*.
%
... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | mapping_parameters.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/mapping_parameters.m | 23,373 | utf_8 | 59c32ad869cef7d4887bd7f6bd777624 | function varargout = mapping_parameters(varargin)
% MAPPING_PARAMETERS M-file for mapping_parameters.fig
% MAPPING_PARAMETERS, by itself, creates a new MAPPING_PARAMETERS or raises the existing
% singleton*.
%
% H = MAPPING_PARAMETERS returns the handle to a new MAPPING_PARAMETERS or the handle to
% ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | load_xls.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/load_xls.m | 4,845 | utf_8 | 98f040ec0685b024ddf99d454fea770d | function varargout = load_xls(varargin)
% LOAD_XLS M-file for load_xls.fig
% LOAD_XLS, by itself, creates a new LOAD_XLS or raises the existing
% singleton*.
%
% H = LOAD_XLS returns the handle to a new LOAD_XLS or the handle to
% the existing singleton*.
%
% LOAD_XLS('CALLBACK',hObject,eventDa... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | drtool.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/drtool.m | 52,422 | utf_8 | c15180ca46e1dcb99c001125b7429b14 | function varargout = drtool(varargin)
% DRTOOL M-file for drtool.fig
% DRTOOL, by itself, creates a new DRTOOL or raises the existing
% singleton*.
%
% H = DRTOOL returns the handle to a new DRTOOL or the handle to
% the existing singleton*.
%
% DRTOOL('CALLBACK',hObject,eventData,handles,...) ... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | plot12n.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/plot12n.m | 1,318 | utf_8 | d01421c22964c2a3a5ae9dd99d026708 | % This file is part of the Matlab Toolbox for Dimensionality Reduction v0.7.2b.
% The toolbox can be obtained from http://homepage.tudelft.nl/19j49
% You are free to use, change, or redistribute this code in any way you
% want for non-commercial purposes. However, it is appreciated if you
% maintain the name of the or... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | not_loaded.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/not_loaded.m | 7,513 | utf_8 | 749124a9066ce5eec69372e3d16cd9d1 | function varargout = not_loaded(varargin)
% NOT_LOADED M-file for not_loaded.fig
% NOT_LOADED by itself, creates a new NOT_LOADED or raises the
% existing singleton*.
%
% H = NOT_LOADED returns the handle to a new NOT_LOADED or the handle to
% the existing singleton*.
%
% NOT_LOADED('CALLBACK',... |
github | UMD-ISL/Matlab-Toolbox-for-Dimensionality-Reduction-master | load_data.m | .m | Matlab-Toolbox-for-Dimensionality-Reduction-master/gui/load_data.m | 6,360 | utf_8 | e87e4a8d82078cbbec95c41a786cd407 | function varargout = load_data(varargin)
% LOAD_DATA M-file for load_data.fig
% LOAD_DATA, by itself, creates a new LOAD_DATA or raises the existing
% singleton*.
%
% H = LOAD_DATA returns the handle to a new LOAD_DATA or the handle to
% the existing singleton*.
%
% LOAD_DATA('CALLBACK',hObject... |
github | RainerKuemmerle/csm-master | sm_display.m | .m | csm-master/misc/rsm/sm_display.m | 3,459 | utf_8 | 2e2d72f8d06cb6df30c7057c84590377 | function [laser_ref, laser_sens] = sm_display(file)
cells = readFileInCells(file);
%global cells
[rows, columns] = size(cells)
% todo: remove comments
r = 1
r = skip_to(cells, r,'laser')
[r, laser_ref] = read_laser_data(cells, r);
r = skip_to(cells, r,'laser')
[r, laser_sens] = read_laser_data(cells, r);
f = fig... |
github | RainerKuemmerle/csm-master | ld_fisher_ext2.m | .m | csm-master/misc/matlab/matlab_new/ld_fisher_ext2.m | 1,010 | utf_8 | 37b9f6c631d0ded9295c14902c4fc8de | function I0 = ld_fisher_ext(ld)
% This is an extension of function ld_fisher0 which does not use the
% (1/cos(beta)) factor.
%
% This function computes Fisher's information matrix, in robot coordinates.
% Uses field 'true_alpha' (and 'theta', 'readings').
%
% For details about the Fisher's information matrix for lo... |
github | RainerKuemmerle/csm-master | ld_fisher_ext.m | .m | csm-master/misc/matlab/matlab_new/ld_fisher_ext.m | 1,274 | utf_8 | 0cdc71a7be93f1df21dd3b5ba40a864c | function I0 = ld_fisher_ext(ld, vars)
% This is an extension of function ld_fisher0 which takes into account
% different variances for each ray. It also does not count rays
% for which ld.valid(i) is set to 0.
%
% This function computes Fisher's information matrix, in robot coordinates.
% Uses field 'true_alpha' (and '... |
github | RainerKuemmerle/csm-master | ld_fisher0.m | .m | csm-master/misc/matlab/matlab_new/ld_fisher0.m | 878 | utf_8 | 73bc90b8476f135fd7e0e735964bdd00 | function I0 = ld_fisher0(ld)
% This function computes Fisher's information matrix, in robot coordinates.
% Uses field 'true_alpha' (and 'theta', 'readings').
%
% For details about the Fisher's information matrix for localization,
% please see this paper: http://purl.org/censi/2006/accuracy
I0 = zeros(3,3);
for i=1... |
github | RainerKuemmerle/csm-master | MbICP.m | .m | csm-master/misc/matlab/mbicp/MbICP.m | 5,682 | utf_8 | c0d3575f7d1fb68f9e9e0213a1a51222 | % Test implementation of Minguez et al Metric Based ICP
% by Patric Jensfelt, 2006-03-28
%
% refScan - 361 range readings from reference scan
% newScan - 361 range readings from reference scan
% initQ - initial estimate of transformation from ref to new scan
%
function transf = MbICP(refScan, newScan, initQ, interac... |
github | RainerKuemmerle/csm-master | deriv.m | .m | csm-master/misc/matlab/utils/deriv.m | 250 | utf_8 | 4b60d67a9483aa7ce5977a8983e0b9ae | %% Numerical derivation with step \verb|epsilon|
function res = deriv(fh, x, epsilon)
% deriv(fh, x, epsilon)
% fh: function handle
% x: point to derive
% epsilon: interval
f1 = fh(x+epsilon/2);
f0 = fh(x-epsilon/2);
res= (f1-f0)/epsilon;
|
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