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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 |
|---|---|---|---|---|---|---|---|---|
github | jaydavey/MEAM620_Proj3-master | shortestpath.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/shortestpath.m | 6,474 | utf_8 | fad7c85c2be0bb8374518b99b879b4b2 | function [path, cost] = shortestpath(Graph, start, goal)
% SHORTESTPATH Find the shortest path from start to goal on the given Graph.
% PATH = SHORTESTPATH(Graph, start, goal) returns an M-by-1 matrix, where each row
% consists of the node on the path. The first
% row is start and the last row is goal. If no pa... |
github | jaydavey/MEAM620_Proj3-master | createAdjecencyMatrix.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/createAdjecencyMatrix.m | 535 | utf_8 | 55f2ac82bde252ac2a1632559be1f4a5 |
function adjMatrix = createAdjecencyMatrix(Graph)
%First, create the matrix. To do this, we need to find the maximum
%number of nodes. We do this by finding the maximum number on columns
%#1 and #2 of the Graph Nx3 Matrix.
num_nodes = max(max(Graph(:,1:2)));
%The following is done to add each element on thei diagona... |
github | jaydavey/MEAM620_Proj3-master | load_map.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/load_map.m | 7,443 | utf_8 | 1840182dcf6d67499087b5521e2f41d2 | function map = load_map(filename, xy_res, z_res, margin)
% LOAD_MAP Load a map from disk.
% MAP = LOAD_MAP(filename, xy_res, z_res, margin). Creates an occupancy grid
% map where a node is considered fill if it lies within 'margin' distance of
% on abstacle.
map = cell(3);
%0.) Read the textfile. This function wi... |
github | jaydavey/MEAM620_Proj3-master | collide_test.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/collide_test.m | 1,593 | utf_8 | 917e064cbc251e91e2f31c7984a0924b | function tests = collide_test
tests = functiontests(localfunctions);
end
function assertNoCollision(testcase, map, points)
c = collide(map, points);
verifyEqual(testcase, size(points, 1), length(c(:)));
verifyFalse(testcase, any(c));
end
function assertCollision(testcase, map, points)
c = collide(map, points);
verify... |
github | jaydavey/MEAM620_Proj3-master | dijkstra.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/dijkstra.m | 10,186 | utf_8 | 4f64d7e48756edd56d8facf06762a0da | function [path, cost] = dijkstra(map, start, goal, astar)
% DIJKSTRA Find the shortest patha from start to goal.
% patha = DIJKSTRA(map, start, goal) returns an M-by-3 matrix, where each row
% consists of the (x, y, z) coordinates of a point on the patha. The first
% row is start and the last row is goal. If no... |
github | jaydavey/MEAM620_Proj3-master | dijkstra_test.m | .m | MEAM620_Proj3-master/Phase 2/A_Star/dijkstra_test.m | 992 | utf_8 | 7edc0abcec621ad052356036f040d60c | function tests = dijkstra_test
tests = functiontests(localfunctions);
end
function assertPathValid(testcase, map, path, start, stop, xlim, ylim, zlim)
valid = xlim(1) <= path(:, 1) & path(:, 1) <= xlim(2);
valid = ylim(1) <= path(:, 2) & path(:, 2) <= ylim(2) & valid;
valid = zlim(1) <= path(:, 3) & path(:, 3) <= zlim... |
github | isetbio/RemoteDataToolbox-master | rdtConfiguration.m | .m | RemoteDataToolbox-master/api/utilities/rdtConfiguration.m | 4,792 | utf_8 | 4cec2ca650852489538f4fb9741ba184 | function [configuration, flavor] = rdtConfiguration(varargin)
%% Initialize a struct with RemoteDataToolbox configuration.
%
% This function initializes a config struct that you can pass to other
% toolbox functions. Config fields start out with default values declared
% in this function. These may be amended with va... |
github | isetbio/RemoteDataToolbox-master | rdtLoadWellKnownFileTypes.m | .m | RemoteDataToolbox-master/api/utilities/rdtLoadWellKnownFileTypes.m | 1,261 | utf_8 | 6ce505e486c4823b4304436e6e114a99 | function data = rdtLoadWellKnownFileTypes(artifact)
%% Load well-known file types, otherwise return file name
%
% data = rdtLoadWellKnownFileTypes(artifact)
% loads data from the given fetched artifact, if the artifact.type is
% well-known (mat, json, or image).
% Otherwise, returns artifact.localPath as a string.
... |
github | isetbio/RemoteDataToolbox-master | rdtCredentialsDialog.m | .m | RemoteDataToolbox-master/api/utilities/rdtCredentialsDialog.m | 2,370 | utf_8 | ef978fdfcbcced91c415a83768c3d570 | function configuration = rdtCredentialsDialog(configuration)
%% Initialize RemoteDataToolbox configuration and prompt for credentials.
%
% This function allows you to enter a username and password for use with
% Remote Data Toolbox, without typing your password into the command
% window. Others may be able to read wha... |
github | isetbio/RemoteDataToolbox-master | rdtFilterStructArray.m | .m | RemoteDataToolbox-master/api/utilities/rdtFilterStructArray.m | 2,792 | utf_8 | 1cd9be23cfbdab20478c6f3c4b9790fe | function [selector, structArray] = rdtFilterStructArray(structArray, fieldName, fieldValue, varargin)
%% Filter a struct array, passing elements that match a given field value.
%
% structArray = rdtFilterStructArray(structArray, fieldName, fieldValue)
% filters the elements of the given structArray, passing only those
... |
github | isetbio/RemoteDataToolbox-master | rdtRequestWeb.m | .m | RemoteDataToolbox-master/api/utilities/rdtRequestWeb.m | 6,526 | utf_8 | 5355b64c26debc9adea3f2b55418910f | function response = rdtRequestWeb(configuration, resourcePath, varargin)
%% Make an HTTP request to a Web server.
%
% response = rdtRequestWeb(configuration, resourcePath) performs an HTTP
% GET request to the server at configuration.serverUrl with the given
% resourcePath.
%
% For example, if configuration.serverUrl i... |
github | isetbio/RemoteDataToolbox-master | rdtDeleteRemotePaths.m | .m | RemoteDataToolbox-master/api/artifacts/rdtDeleteRemotePaths.m | 3,881 | utf_8 | de9d5d38539798c9ed123d2207623860 | function [deleted, notDeleted] = rdtDeleteRemotePaths(configuration, remotePath, varargin)
%% Delete paths containing artifacts from a remote server and the local cache.
%
% [deleted, notDeleted] = rdtDeleteRemotePaths(configuration, remotePath)
%
% Deletes one or more paths containing artifacts from a remote server ... |
github | isetbio/RemoteDataToolbox-master | rdtDeleteArtifacts.m | .m | RemoteDataToolbox-master/api/artifacts/rdtDeleteArtifacts.m | 4,506 | utf_8 | 39cb3fe422feda2ed1da099dcc2b5009 | function [deleted, notDeleted] = rdtDeleteArtifacts(configuration, artifacts, varargin)
%% Delete multiple artifacts from a remote server and the local cache.
%
% [deleted, notDeleted] = rdtDeleteArtifacts(configuration, artifacts)
% deletes multiple artifacts from a remote server and from the local
% artifact cache. ... |
github | isetbio/RemoteDataToolbox-master | rdtRequestRescan.m | .m | RemoteDataToolbox-master/api/queries/rdtRequestRescan.m | 3,482 | utf_8 | 69e4c3751267328be83e6f70467712e1 | function [isStarted, message] = rdtRequestRescan(configuration, varargin)
%% Request Archiva to re-scan a repository for artifact listings.
%
% [isStarted, message] = rdtRequestRescan(configuration) requests a
% repository re-scan from an Archiva Maven repository. If successful, this
% will cause the repository artifa... |
github | isetbio/RemoteDataToolbox-master | rdtListLocalArtifacts.m | .m | RemoteDataToolbox-master/api/queries/rdtListLocalArtifacts.m | 5,548 | utf_8 | aa0f57b265a2fc850236421ce3ebebdd | function artifacts = rdtListLocalArtifacts(configuration, remotePath, varargin)
%% Query locally cached artifacts under the given remotePath.
%
% artifacts = rdtListLocalArtifacts(configuration, remotePath) builds a
% list of all locally cached artifacts originating from the given
% remotePath. configuration.cacheFolde... |
github | isetbio/RemoteDataToolbox-master | savejson.m | .m | RemoteDataToolbox-master/external/jsonlab/savejson.m | 14,325 | utf_8 | 9261f7b11300ca86f9593aaf9a2a61c4 | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | isetbio/RemoteDataToolbox-master | loadjson.m | .m | RemoteDataToolbox-master/external/jsonlab/loadjson.m | 16,244 | ibm852 | d2a14cf9daff576db152ed2622d30cc5 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% date: 2011/09/09
% Nedialko Krouchev: http:... |
github | isetbio/RemoteDataToolbox-master | loadubjson.m | .m | RemoteDataToolbox-master/external/jsonlab/loadubjson.m | 13,720 | utf_8 | ef8f70c28ebff48f1b1a118b2471a101 | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% date: 2013/08/01
%
% $Id: loadubjson.m 410 20... |
github | isetbio/RemoteDataToolbox-master | saveubjson.m | .m | RemoteDataToolbox-master/external/jsonlab/saveubjson.m | 15,013 | utf_8 | 224ebec1f724546135d9d78bdde79646 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | isetbio/RemoteDataToolbox-master | urlread2.m | .m | RemoteDataToolbox-master/external/V1_1_urlread2/urlread2.m | 14,027 | utf_8 | 280fa630d402a9bc7acb5d8b45a10daf | function [output,extras] = urlread2(urlChar,method,body,headersIn,varargin)
%urlread2 Makes HTTP requests and processes response
%
% [output,extras] = urlread2(urlChar, *method, *body, *headersIn, varargin)
%
% * indicates optional inputs that must be entered in place
%
% UNDOCUMENTED MATLAB VERSION
%
%... |
github | isetbio/RemoteDataToolbox-master | gradleFetchArtifact.m | .m | RemoteDataToolbox-master/external/gradle/gradleFetchArtifact.m | 5,816 | utf_8 | 10337d4a1483b8f0bda47c63d9c4c0ea | function [filePath, pomPath, downloads] = gradleFetchArtifact(repository, username, password, group, id, version, extension, varargin)
%% Use Gradle to fetch an artifact from a Maven repository.
%
% filePath = gradleFetchArtifact(repository, username, password, group, id, version, extension)
% fetches an artifact from ... |
github | isetbio/RemoteDataToolbox-master | passwordEntryDialog.m | .m | RemoteDataToolbox-master/external/passwordEntryDialog/passwordEntryDialog.m | 15,137 | utf_8 | 90ce3329a09f02f03b08eab0776b7e75 | function [Password, UserName] = passwordEntryDialog(varargin)
% PASSWORDENTRYDIALOG
% [Password, UserName] = passwordEntryDialog(varargin)
%
% Create a password entry dialog for entering a password that is visibly
% hidden. Java must be enabled for this function to work properly.
%
% It has only been tested on ... |
github | ikarosilva/wfdb-app-toolbox-master | wfdbdesc.m | .m | wfdb-app-toolbox-master/mcode/wfdbdesc.m | 7,432 | utf_8 | 2ae53f9bd2c113b69ccc41056a7bf0e4 | function varargout=wfdbdesc(varargin)
%
% [siginfo,Fs,sigClass]=wfdbdesc(recordName)
%
% Wrapper to WFDB WFDBDESC:
% http://www.physionet.org/physiotools/wag/wfdbde-1.htm
%
% Reads a WFDB record metadata and returns:
%
%
% siginfo
% Nx1 vector of structures with the following fields:
%
% LengthSa... |
github | ikarosilva/wfdb-app-toolbox-master | wrann.m | .m | wfdb-app-toolbox-master/mcode/wrann.m | 6,651 | utf_8 | 81e5ba6cdf97b6e9dd24fc5e35f68986 | function varargout=wrann(varargin)
%
% wrann(recordName,annotator,ann,anntype,subtype,chan,num,comments)
%
% Wrapper to WFDB WRANN:
% http://www.physionet.org/physiotools/wag/wrann-1.htm
%
% Writes data into a WFDB annotation file. The file will be saved at the
% current directory (if the record is in the cu... |
github | ikarosilva/wfdb-app-toolbox-master | bxb.m | .m | wfdb-app-toolbox-master/mcode/bxb.m | 4,425 | utf_8 | 344e72b93a2941c57e6e694502e53ab1 | function varargout=bxb(varargin)
%
% report=bxb(recName,refAnn,testAnn,reportFile,beginTime,stopTime,matchWindow)
%
% Wrapper to WFDB BXB:
% http://www.physionet.org/physiotools/wag/bxb-1.htm
%
% Creates a report file ("reportFile) using
% ANSI/AAMI-standard beat-by-beat annotation comparator.
%
% Ouput Para... |
github | ikarosilva/wfdb-app-toolbox-master | surrogate.m | .m | wfdb-app-toolbox-master/mcode/surrogate.m | 1,986 | utf_8 | 4dce61f40839e472d48a46aa980d311b | function Y=surrogate(x,M)
%
% Y=surrogate(x,M)
%
% Generates M amplitude adjusted phase shuffled surrogate time series from x.
% Useufel for testing the underlying assumption that the null hypothesis consists
% of linear dynamics with possibly non-linear, monotonically increasing,
% measurement function.
%
% Required ... |
github | ikarosilva/wfdb-app-toolbox-master | mat2wfdb.m | .m | wfdb-app-toolbox-master/mcode/mat2wfdb.m | 19,588 | utf_8 | 82c1a4fa8dd0b346e195dee4fd234e3b | function [varargout]=mat2wfdb(varargin)
%
% [xbit]=mat2wfdb(X,fname,Fs,bit_res,adu,info,gain,sg_name,baseline,isquant, isdigital)
%
% Convert data from a matlab array into Physionet WFDB format file.
%
% Input Paramater are:
%
% X -(required) NxM matrix of M signals with N samples each. The
% ... |
github | ikarosilva/wfdb-app-toolbox-master | wfdbloadlib.m | .m | wfdb-app-toolbox-master/mcode/wfdbloadlib.m | 8,307 | utf_8 | 827524c29ba802faed32b8f9f0b270d5 | function [varargout]=wfdbloadlib(varargin)
%
% [isloaded,config]=wfdbloadlib(debugLevel,networkWaitTime)
%
% Loads the WDFDB libarary if it has not been loaded already into the
% MATLAB classpath. And optionally prints configuration environment and debug information
% regarding the settings used by the classes in the J... |
github | ikarosilva/wfdb-app-toolbox-master | woody.m | .m | wfdb-app-toolbox-master/mcode/woody.m | 6,844 | utf_8 | 9c2addac71de53103bc68ce2211515a6 | function [out]=woody(x,varargin)
%
% [out]=woody(x,tol,max_it,est_mthd,xcorr_mthd)
%
% Weighted average using Woody average for a signal
% with jitter. Parameters:
%
% x Signal measurements. Each COLUMN represents
% and independent measure of the signal (or channel).
% tol T... |
github | ikarosilva/wfdb-app-toolbox-master | wfdbRecordViewer.m | .m | wfdb-app-toolbox-master/mcode/wfdbRecordViewer.m | 52,950 | utf_8 | 6eec979ea39d95fc867c59f7e5462e7f | function varargout = wfdbRecordViewer(varargin)
% WFDBRECORDVIEWER MATLAB code for wfdbRecordViewer.fig
% WFDBRECORDVIEWER, by itself, creates a new WFDBRECORDVIEWER or raises the existing
% singleton*.
%
% H = WFDBRECORDVIEWER returns the handle to a new WFDBRECORDVIEWER or the handle to
% the exis... |
github | alexschlegel/mentalrotation-master | Prepare.m | .m | mentalrotation-master/code/@MentalRotation/Prepare.m | 2,073 | utf_8 | b121abf904d56342b4541e8779cefc30 | function Prepare(mr,varargin)
% MentalRotation.Prepare
%
% Description: prepare to run a mentalrotation experiment
%
% Syntax: mr.Prepare()
%
% Updated: 2014-02-07
% Copyright 2014 Alex Schlegel (schlegel@gmail.com). This work is licensed
% under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
% L... |
github | alexschlegel/mentalrotation-master | Trial.m | .m | mentalrotation-master/code/@MentalRotation/Trial.m | 4,461 | utf_8 | adacd285891bc3d7282cedc3c5e4f078 | function res = Trial(mr,kRun,kTrial,varargin)
% MentalRotation.Trial
%
% Description: run a MentalRotation trial
%
% Syntax: res = mr.Trial(kRun,kTrial,[tStart]=<now>,<options>)
%
% In:
% kRun - the run number
% kTrial - the trial number
% tStart - the start time, in TRs. if unspecified, the trial starts
% imme... |
github | alexschlegel/mentalrotation-master | ShowGuide.m | .m | mentalrotation-master/code/@MentalRotation/ShowGuide.m | 2,419 | utf_8 | 949b537ab4313d6de9e0355fcdda0eef | function ShowGuide(mr,kRun,kTrial)
% MentalRotation.ShowGuide
%
% Description: show the helper for the specified trial and wait for a responses
%
% Syntax: mr.ShowGuide(kRun,kTrial)
%
% In:
% kRun - the current run
% kTrial - the current trial
%
% Updated: 2014-02-08
% Copyright 2014 Alex Schlegel (schlegel@gmail.... |
github | alexschlegel/mentalrotation-master | Run.m | .m | mentalrotation-master/code/@MentalRotation/Run.m | 4,309 | utf_8 | ad579eae3309dddaaf5e984139d93d51 | function Run(mr)
% MentalRotation.Run
%
% Description: do the next mentalrotation run
%
% Syntax: mr.Run
%
% Updated: 2014-02-08
% Copyright 2014 Alex Schlegel (schlegel@gmail.com). This work is licensed
% under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
% License.
nRun = MR.Param('exp','runs... |
github | alexschlegel/mentalrotation-master | SubjectInfo.m | .m | mentalrotation-master/code/+MR/SubjectInfo.m | 11,695 | utf_8 | 48d28dad1051f4e75f338f2aa21a5bb5 | function s = SubjectInfo(varargin)
% MR.SubjectInfo
%
% Description: compile a struct of subject info
% NOTE: Updated so that the mvpa labeling code makes more sense
% and includes all 5 test TRs.
%
%
% Syntax: s = MR.SubjectInfo(<options>)
%
% In:
% <options>:
% subject: (<all>) ... |
github | alexschlegel/mentalrotation-master | GetFigure.m | .m | mentalrotation-master/code/+MR/GetFigure.m | 2,398 | utf_8 | d1ee4f66eaa49c3e0bdf3fe60ea47c50 | function varargout = GetFigure(varargin)
% MR.GetFigure
%
% Description:
%
% Syntax: MR.GetFigure (first call)
% im = MR.GetFigure(id,<options>)
%
% In:
% id - the figure id
% <options>:
% operation: (<none>) the operation to perform on the image. one of 'l',
% 'r', 'b', or 'f'.
% flip: (false) true to fl... |
github | alexschlegel/mentalrotation-master | Translate.m | .m | mentalrotation-master/code/+MR/Translate.m | 805 | utf_8 | 950a375e21e2101220d8660d29dca764 | function y = Translate(x)
% MR.Translate
%
% Description: translate strings for presentation
%
% Syntax: y = MR.Translate(x)
%
% Updated: 2014-03-06
% Copyright 2014 Alex Schlegel (schlegel@gmail.com). This work is licensed
% under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
% License.
per... |
github | reklab/reklab_public-master | basisinput.m | .m | reklab_public-master/stiffnessID/basisinput.m | 946 | utf_8 | cf1a52170a6e45dff020ca3487a766e6 | % change the input to satisfy the requirement.
function [U ] = basisinput(u,n)
% this function is to generate the Chebshev polynomial terms
% of the input that is used to identify Hammerstein system.
% u is the input signal
% y is the constructed inputs
% n is the order of the Chebshev polynomical
if nargin ==0
... |
github | reklab/reklab_public-master | OS_stiffnessID.m | .m | reklab_public-master/stiffnessID/OS_stiffnessID.m | 14,998 | utf_8 | fc38088bcae07bff29db67e5799e7b77 | function [system_ss, K, B, I, tqR, tqI, tqT]= SSY_stiffnessId (z,varargin)
% This function estimates a parallel-cascade model between input and output stored in columns of z.
% The identification is based on :
%
%Y Zhao and D. T. Westwick and R. E. Kearney "Subspace Methods for
%Identification of Human Ankle Joint Sti... |
github | reklab/reklab_public-master | simulate_PC_ShortSegment.m | .m | reklab_public-master/stiffnessID/simulate_PC_ShortSegment.m | 5,425 | utf_8 | 77aef251d7a2e6891c9ae35b9996c92e | function [trqIntrinsicPredict,trqReflexPredict,trqTotalPredict,idVAF,posMeasured,trqMeasured] = simulate_PC_ShortSegment(intrinsic,reflex,z)
%This function simulates the PC system to segdat inputs
%It identifies initial conditions as part of the simulation
decimationRatio = 1;
zn=nldat(z)
position = zn(:,1);
position =... |
github | reklab/reklab_public-master | SS_SDSS_stiffnessID.m | .m | reklab_public-master/stiffnessID/SS_SDSS_stiffnessID.m | 16,521 | utf_8 | 2aac99e7e5419619f9aa4b48716a5651 | function [intrinsic, reflex, tqI, tqR, tqT, vafs] = SS_SDSS_stiffnessID (z,varargin)
% [intrinsic, reflex, tqI, tqR, tqT, vafs] = SS_SDSS_stiffnessID (z)
% This function requires NLID toolbox in MATLAB path
% This function estimates parallel-cascade joint stiffness between input and output
% from short segments of ... |
github | reklab/reklab_public-master | SS_stiffnessID.m | .m | reklab_public-master/stiffnessID/SS_stiffnessID.m | 15,320 | utf_8 | 7b3f10ec7b3b47e3e3faf6e2e58988af | function [system_ss,pIntrinsic, tqPredicted]= SS_stiffnessID (z,varargin)
% This function estimates a parallel-cascade model between input and output stored in columns of z.
% The identification is based on :
%
%Y Zhao and D. T. Westwick and R. E. Kearney "Subspace Methods for
%Identification of Human Ankle Joint Sti... |
github | reklab/reklab_public-master | pcDemo.m | .m | reklab_public-master/stiffnessID/pcDemo.m | 2,258 | utf_8 | ee841669d6d7f00a8adda2aff8828db2 | function pcDemo
%% Demonstrate various aproaches to the identificatio of the parallel cascad emode
load experimental_data.mat
z=z_pf2;
%% Rectifier followed by IRF
reflexIdMethod='rect';
[hIntrinsic, mReflex, nlmStiff, VAFT, VAFi, VAFr, tqI, tqR, tqT]= PC_stiffnessID (z,'reflex_id_method',reflexIdMethod);
figNum=1;
... |
github | reklab/reklab_public-master | cestbd.m | .m | reklab_public-master/smi-2.0-devel/cestbd.m | 2,952 | utf_8 | 01f865ba984a178d44f3cfaf6a99ea00 |
function [B,D,x0,K,R,Phi] = cestbd(u,y,Ts,A,C,model,Rold);
% cestbd Estimates the matrices B and D of the state space model
%
% .
% x(t) = Ax(t) + Bu(t) + w(t)
% y(t) = Cx(t) + Du(t) + v(t)
% using the knowledge of the pair A, C. This function e... |
github | reklab/reklab_public-master | crslslin.m | .m | reklab_public-master/smi-2.0-devel/crslslin.m | 11,077 | utf_8 | d4ffa32743c351bcab2059f7f2f31e25 |
function [A,B,C,D,hist] = crslslin(A,C,K,u,y,model,options,slsstate)
% crslslin This function performs a recursive update of a discrete time
% state space system,
% x(k+1) = A x(k) + B u(k)
% y(k) = C x(k) + D u(k) + v(k
% using the Seperable Le... |
github | reklab/reklab_public-master | drslslin.m | .m | reklab_public-master/smi-2.0-devel/drslslin.m | 15,262 | utf_8 | 5008900c52f4545ff5f147079ab67d90 |
function [A,B,C,D,K,hist] = drslslin(u,y,A,C,K,model,partype,options,slsstate)
% drslslin This function performs a recursive update of a discrete time
% state space system,
% x(k+1) = A x(k) + B u(k)
% y(k) = C x(k) + D u(k) + v(k)
% using the S... |
github | reklab/reklab_public-master | dss2th.m | .m | reklab_public-master/smi-2.0-devel/dss2th.m | 6,905 | utf_8 | 85c18b2dd456cb407fef0ba095412b47 |
function [theta,params,T] = dss2th(varargin)
% dss2th This function converts a discrete time state space
% model to a parameter vector that describes the model
% Model structure:
% x(k+1) = Ax(k) + Bu(k) + Ke(k)
% y(k) = Cx(k) + Du(k) + e(k)
% Syntax:
%... |
github | reklab/reklab_public-master | cslslin.m | .m | reklab_public-master/smi-2.0-devel/cslslin.m | 4,811 | utf_8 | 4479d9a4766da0d757f639dfb7f5bc67 |
function [A,B,C,D,x0,K,options] = cslslin(u,y,Ts,A,C,K,model,partype,options)
% cslslin Performs a Least Squares optimization of a continuous
% time linear state space system system with model
% structure:
% .
% x(t) = Ax(t) + Bu(t)
% y... |
github | reklab/reklab_public-master | dslslin.m | .m | reklab_public-master/smi-2.0-devel/dslslin.m | 4,716 | utf_8 | 36912689676698cc9bec79eee1b50564 |
function [A,B,C,D,x0,K,options] = dslslin(u,y,A,C,K,model,partype,options)
% dslslin Performs a Least Squares optimization of a discrete
% time linear state space system system with model
% structure:
%
% x(k+1) = Ax(k) + Bu(k) + Ke(k)
% y(k) = Cx(k) + Du(k) + ... |
github | reklab/reklab_public-master | dslswie.m | .m | reklab_public-master/smi-2.0-devel/dslswie.m | 4,555 | utf_8 | 31c9dc48eca4598831e96be54bb30840 |
function [A,B,C,D,x0,thl,options] = dslswie(u,z,A,B,C,D,x0,nn,model, ...
partype,options)
% dslswie Performs a Least Squares optimization of a discrete
% time Wiener state space system system with model
% structure:
% x(k+1) = Ax(k) + Bu(k)
% y(k... |
github | reklab/reklab_public-master | css2th.m | .m | reklab_public-master/smi-2.0-devel/css2th.m | 7,367 | utf_8 | 62e4d2dcc33a4e73c47df1344aa687fc |
function [theta,params,T] = css2th(varargin);
% css2th This function converts a continuous time state space
% model to a parameter vector that describes the model.
% Model structure
% .
% x(t) = Ax(t) + Bu(t)+ K e(t)
% y(t) = Cx(t) + Du(t) + e(t) ... |
github | reklab/reklab_public-master | cordom.m | .m | reklab_public-master/smi-2.0-devel/cordom.m | 5,717 | utf_8 | 079432fa6e1ac105a5d634678f554365 |
function [Sn,Rnew] = cordom(u,y,t,a,i,Rold);
% cordom Delivers information about the order of a LTI
% continuous time state space model and acts as a
% pre-processor for cestac. The latter actually estimates
% the system matrices A and C.
% Model structure:
% .... |
github | reklab/reklab_public-master | kroneckf.m | .m | reklab_public-master/smi-2.0-devel/kroneckf.m | 19,556 | utf_8 | c480c4f3679e3ef3247d1e5d88cd6440 | function [AA,BB,Q,Z,na,nb]=kroneckf(A,B,alpha,option);
% kroneckf Calculates the Kronecker canonical form from a regular
% pencil A, B such that
% | Ak 0 |
% Q*A*Z=AA= | I |
% and
% ... |
github | reklab/reklab_public-master | dordom.m | .m | reklab_public-master/smi-2.0-devel/dordom.m | 3,673 | utf_8 | 6fd82aa23a3d43a0785f624aacb797ca |
function [Sn,R] = dordom(u,y,i,R);
% dordom is a preprocessor function that extracts the column-space of
% the extended observability matrix from input/output data. Data from
% different experiments can be concatenated using the extra input
% argument R. The estimated column-space is u... |
github | reklab/reklab_public-master | nlid_resid.m | .m | reklab_public-master/nlid_tools/nlid_resid.m | 2,747 | utf_8 | e9b86a8f63f26c717d8966c6522fe72a | function [R, V, yp] = nlid_resid( M, z, varargin);
% NLID_RESID - compute and display prediction error in model output.
% Usage:
% [R, V, yp] = nlid_resid( M, z, plotFlag);
% R - residuals
% V - variance accoutned for
% yp - pedicted otuput
%
% M - model
% z - inpout output dats
% Multiple realizatio... |
github | reklab/reklab_public-master | nlid_help.m | .m | reklab_public-master/nlid_tools/nlid_help.m | 23,798 | utf_8 | 7e8243829735319005dc51bdb0a9c840 | function nlid_help(option)
% NLID_HELP - generate help on the classes for nlid_tools
% option
% ' buildHelp - build extended html help file' ...
% classList - list of all classes for nlid_tools' ...
% help = display detailed help file' ...
% classname - help on methods for class' ...
%
% Usage
% nlid_h... |
github | reklab/reklab_public-master | tvIRFidentBasisExpansion.m | .m | reklab_public-master/nlid_tools/@tvm/tvIRFidentBasisExpansion.m | 4,284 | utf_8 | 988b5d15d6b8c3a73b0ec9d033190c4d |
end
function [H, x_pred, Extra] = np_TV_ident(X, Y, Basis, varargin)
% Identifies dynamics of linear, time-varying, non-parametric system.
% Diegos method
% [H, x_pred] = np_TV_ident(X, Y, varargin)
%
% X: input matrix
% Y: output matrix
% Basis: Basis functions
% Additional argume... |
github | reklab/reklab_public-master | tv_irf_ident_expansion.m | .m | reklab_public-master/nlid_tools/@tvm/private/tv_irf_ident_expansion.m | 4,319 | utf_8 | 9d7c582cf5d4250fe114a54eb728aaf2 |
function [H, x_pred, Extra] = np_TV_ident(X, Y, Basis, nLags, nSides, domainIncr, periodic, method)
% Identifies dynamics of linear, time-varying, non-parametric system.
% Diegos method
% [H, x_pred] = np_TV_ident(X, Y, varargin)
%
% X: input matrix
% Y: output matrix
% Basis: Basis ... |
github | reklab/reklab_public-master | pcas2wiener.m | .m | reklab_public-master/nlid_tools/nlid_util/pcas2wiener.m | 2,225 | utf_8 | f0ae573a5604fb2ff90df832a57c40e0 | function wskernel = pcas2wiener(pc_system,order,sigma_u);
% compute first and second-order Wiener kernels of an LNL system
%
% syntax: wskernel = lnl2wiener(pc_model,order,sigma_u);
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% Genera... |
github | reklab/reklab_public-master | kernel_convolve.m | .m | reklab_public-master/nlid_tools/nlid_util/kernel_convolve.m | 2,065 | utf_8 | ec747c3c13d80ee59a022eb62925860c | function kernels = kernel_convolve(kerns,subsys)
% KERNEL_CONVOLE - convolve the kernels in kerns with the irf or kernel object in subsys
% kerns is assumed to be a Q element cell array containing kernels of order
% 0 through Q-1
% subsys is assmed to be an irf or volterra kernel.
% $Revision: 1.3 $
% Copyright 2003, ... |
github | reklab/reklab_public-master | combination.m | .m | reklab_public-master/nlid_tools/nlid_util/combination.m | 403 | utf_8 | cf812bb20617aca75423cb51aacce744 | %% This function calculates the number of k-combinations from n objects where the order of selection does not matter (as opposed to permutation).
function y = combination(n,k)
%++ Instead of computationally in-efficient general formula
% y = factorial(n) / (factorial(n-k)*factorial(k));
%++ We use the following m... |
github | reklab/reklab_public-master | eseqDemo.m | .m | reklab_public-master/nlid_tools/nlid_util/eseqDemo.m | 693 | utf_8 | 1108d8e7432e5934b4a36b467411a620 | function eseqDemo
% eseqDemo - domnonsrate properties of the event sequence class
e1= eseq;
for i=1:5;
e1(i,1).startIdx=1+i*20;
e1(i,1).endIdx=e1(i).startIdx+10;
e1(i,1).type='1';
e2(i,1).startIdx=1+(i-1)*20;
e2(i,1).endIdx=e2(i).startIdx+10;
e2(i,1).type='1';
end
% convert to ... |
github | reklab/reklab_public-master | laguerre.m | .m | reklab_public-master/nlid_tools/nlid_util/laguerre.m | 1,062 | utf_8 | 512f51e5d2695d3dbb3222140ce8c8f5 | %% This function generates Laguerre orthonormal basis functions
%++ Author: Ehsan Sobhani (10 April 2014)
%++ This is based on Maremaleris book OR formula (11) of his paper titled:
%++ "Identification of Nonlinear Biological Systems Using Laguerre Expansions of Kernels", Annals of Biomed. Eng., vol. 21, pp. 573-589,... |
github | reklab/reklab_public-master | waveform.m | .m | reklab_public-master/nlid_tools/@waveform/waveform.m | 7,608 | utf_8 | 3f59d15cc90d2ed6411272b7c8919398 | classdef waveform < nltop
% waveform - waveform class for NLID toolbox
% Generates a variety of waveform determined by the parameter 'waveformType';
properties
waveformType=''
parameterSet=param;
end
methods
function sys = waveform (a,varargin)
sys.co... |
github | reklab/reklab_public-master | wkern.m | .m | reklab_public-master/nlid_tools/@wkern/old/wkern.m | 550 | utf_8 | 68eb1113dfc9087a6d3eabe39bb4e314 | function WK = wkkern (z, varargin)
% Wiener kernel model
% Parent: kern
% Copyright 1999-2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
WK=mkwkern;
if nargin==0;
return
els... |
github | reklab/reklab_public-master | pvnl.m | .m | reklab_public-master/nlid_tools/@pvnl/pvnl.m | 6,309 | utf_8 | 923017e792f7ba6f3c9b49c0422993df | classdef pvnl < pvm % pvnl is a subclass of pvm
% pvnl - Parameter varying (PV) static nonlinear model class for NLID toolbox.
% pvnl is a nonlinear static model of input and scheduling variable (SV)
% in which every coefficient of input nonlinearity (polynomial) is a
% static nonlinear (p... |
github | reklab/reklab_public-master | random_sig.m | .m | reklab_public-master/nlid_tools/@nldat/random_sig.m | 2,999 | utf_8 | 8463a129799622ba384c65f8984d41f1 | function Y = random_sig (X , C, NCHANGE, NREPORT );
%
% X - seed signal
% C - desired autocorelation function
% NCHANGE= number of interchanges
% NREPORT -- frequency to report
%
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public Li... |
github | reklab/reklab_public-master | ac_types.m | .m | reklab_public-master/nlid_tools/@nldat/obsolete/ac_types.m | 765 | utf_8 | f5003452209509fb3ec426862bbe3881 | function ac_types
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see copying.txt and gpl.txt
function ac_examples
clf;
nx=4;
ny=2;
% {{{ white noise
tmax=2;incr = .001;
x=nlid_sig('normal', 'meanval', 1.,'sd', 3,... |
github | reklab/reklab_public-master | ddt.m | .m | reklab_public-master/nlid_tools/@nldat/obsolete/ddt.m | 1,682 | utf_8 | 82067929956757ba7db4ff0a64a22bdf | function v = ddt(x)
% ddt function for nldat sets
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see copying.txt and gpl.txt
[nsamp,nchan,nreal]=size(x);
v=x;
xd=x.dataSet;
incr=x.domainIncr;
for ireal=1:nreal,
... |
github | reklab/reklab_public-master | nl2vs.m | .m | reklab_public-master/nlid_tools/@nlbl/nl2vs.m | 1,805 | utf_8 | 23929522980e1f13b82d8e437c964fee | function vs = nl2vs (nl,vsin);
% Convert to Volterra series from nl model description
%
OrderMax = get(vsin,'vsOrderMax');
subsystems = get(nl,'elements');
p = subsystems{1};
p = nlident(p,'polyType','power');
mc=get(p,'polyCoef');
h = double(subsystems{2});
Ts = get(subsystems{2},'domainIncr');
hlen = length(h);
... |
github | reklab/reklab_public-master | poly_rescale.m | .m | reklab_public-master/nlid_tools/@nlbl/private/poly_rescale.m | 4,328 | utf_8 | 79ab61faa2c91de09c7084c8bae8a8a5 | function Mnew = poly_rescale(Mold,PolyInput)
% transforms polynomial coefficients for different input stats
%
% syntax: Mnew = poly_rescape(Mold,PolyInput)
%
%
% Copyright 1999-2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License... |
github | reklab/reklab_public-master | hammer_subspace.m | .m | reklab_public-master/nlid_tools/@nlbl/private/hammer_subspace.m | 7,048 | utf_8 | 77d187ef0fbeb1f6318e4a2a3b0dcdf1 | function system= hammer_subspace (z,N)
% This function estimates a Hammerstein between input and output stored in columns of z.
% This function uses MOESP subspace approach
%
% syntax: system= hammer_subspace (z)
% where:
% N is a nlbl object containing a hammerstein cascade.
% z is an nldat objects conta... |
github | reklab/reklab_public-master | nlsim_hammer_subspace_short_segment.m | .m | reklab_public-master/nlid_tools/@nlbl/private/nlsim_hammer_subspace_short_segment.m | 3,098 | utf_8 | 45e66db00b9337757eb81b50cebd5f91 | function output_predicted = nlsim_hammer_subspace_short_segment (sys,z)
%This function estimates output of a hammerstein system based on short segments of input
%and output
%system= nlsim_hammer_subspace_short_segment (z)
%This routine is based on the following work:
%Kian Jalaleddini, Ferryl Alley, Robert E Kearney, "... |
github | reklab/reklab_public-master | hammer_subspace_short_segment.m | .m | reklab_public-master/nlid_tools/@nlbl/private/hammer_subspace_short_segment.m | 10,940 | utf_8 | 9743c4358104e817790792f453ff4bd2 | function system_nlbl = hammer_subspace_short_segment (z,ps)
%This function estimates a hammerstein system based on short segments of input
%and output
%system= hammer_subspace_short_segment (z,ps)
%This routine is based on the following work:
%Kian Jalaleddini, Ferryl Alley, Robert E Kearney, "Identification of
%Hammer... |
github | reklab/reklab_public-master | pcm_nlls.m | .m | reklab_public-master/nlid_tools/@pcascade/private/pcm_nlls.m | 5,057 | utf_8 | 182fd5c8efb1a8e6d7fd97c102e20acd | function pc = pcm_nlls(pc,z);
% nonlinear least squares optimization methods to fit parallel cascade
% models. Normally called from nlident.m
% 1 extract data and tuning parameters.
u = z(:,1);
y = z(:,2);
N = length(y);
Ts = get(u,'domainIncr');
P = getParamValStruct(pc.parameterSet);
% creates variables contain... |
github | reklab/reklab_public-master | pcas2wiener.m | .m | reklab_public-master/nlid_tools/@pcascade/Old/pcas2wiener.m | 2,154 | utf_8 | bdb02dc7a3902fb5e8dc4a9d75f6418a | function wskernel = pcas2wiener(pc_system,order,sigma_u);
% compute first and second-order Wiener kernels of an LNL system
%
% syntax: wskernel = lnl2wiener(pc_model,order,sigma_u);
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% Genera... |
github | reklab/reklab_public-master | pcascade.m | .m | reklab_public-master/nlid_tools/@pcascade/Old/pcascade.m | 642 | utf_8 | 90b2720274f3367660dccda784b9129b | function PC = pcascade (z, varargin)
% Parallel Cascade Model
% Parent: nlm
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
PC=mkpc;
if nargin==0;
return
elseif ... |
github | reklab/reklab_public-master | pcm_nlls.m | .m | reklab_public-master/nlid_tools/@pcascade/Old/pcm_nlls.m | 4,779 | utf_8 | bc21c1569a98ab832ea3a444a0f9240c | function pc = pcm_nlls(pc,z);
% nonlinear least squares optimization methods to fit parallel cascade
% models. Normally called from nlident.m
% 1 extract data and tuning parameters.
u = z(:,1);
y = z(:,2);
N = length(y);
Ts = get(u,'domainincr');
P = get(pc,'parameters');
assign(P);
% creates variables containing ... |
github | reklab/reklab_public-master | polynom.m | .m | reklab_public-master/nlid_tools/@polynom/polynom.m | 38,806 | utf_8 | 8c31f8aac811290b0d8d3a81bbf0e020 | classdef polynom < nltop
% polynom - polynomial class for NLID toolbox.
% polyRange[-1 1] - inpout range
% - used with tcheb to scale input to range of tceb polynomials. This must be
% set when creating a polynomial apriori
% polyMean [0] - mean of polynomial
% polyStd[1] - standar... |
github | reklab/reklab_public-master | nlident.m | .m | reklab_public-master/nlid_tools/@polynom/Osolete/nlident.m | 6,009 | utf_8 | 51b009bfe8b79a1b81609abbcbc52efb | function p = nlident (pin, z, varargin );
% polynom/nlident - Overlaid nlident for polynom class
global POLY_ORDER POLY_DONE
if isa(z,'char')
% z and varargin are property value pairs
p = nltransform(pin,{z ,varargin{1:end}});
return
end
if ~(isa (z,'double') | isa(z,'nldat'))
error (' Second argume... |
github | reklab/reklab_public-master | poly_convert.m | .m | reklab_public-master/nlid_tools/@polynom/private/poly_convert.m | 4,508 | utf_8 | 433e0ac2e54dbae331dae1ea26b6b86b | function Cnew = poly_convert(C,InputStats,OldType,NewType)
% converts bewteen power, tchebyshev and hermite polynomials
%
% syntax: Cnew = poly_convert(C,InputStats,OldType,NewType)
%
% C is a vector of polynomial coefficients stored in order of increasing
% exponent (UNLIKE polyval)
%
% InputStats = [Xmax, Xmin, X... |
github | reklab/reklab_public-master | lnl2wiener.m | .m | reklab_public-master/nlid_tools/@lnlbl/lnl2wiener.m | 3,493 | utf_8 | b9273644947ea6c9e5e3c41c95978dc2 | function wkernel = lnl2wiener(lnl,hlen,order,sigma_u);
% compute first and second-order Wiener kernels of an LNL system
%
% syntax: wkernel = lnl2wiener(lnl,hlen,order,sigma_u);
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Pu... |
github | reklab/reklab_public-master | lnl2volt.m | .m | reklab_public-master/nlid_tools/@lnlbl/lnl2volt.m | 2,846 | utf_8 | b2f9325b31a6bf7206cbe4ff0a558f82 | function VKernel = lnl2volt(lnl,hlen,order);
% computes Volterra kernels of a lnl cascade.
%
% syntax VKernel = lnl2volt(lnl,hlen,order);
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copyi... |
github | reklab/reklab_public-master | lnlbl.m | .m | reklab_public-master/nlid_tools/@lnlbl/lnlbl.m | 13,138 | utf_8 | 40c6f603509299da846200bb88048420 | classdef lnlbl < nlm
% lnlbl - linear-nonlinear-linear block model class for NLID toolbox.
%% Support for two-side IRFs is still under development.
properties
end
methods
function LNL = lnlbl (a,varargin)
LNL.parameterSet(1)=param('paramName','idMetho... |
github | reklab/reklab_public-master | lnbl.m | .m | reklab_public-master/nlid_tools/@lnlbl/lnbl.m | 637 | utf_8 | ae97f5d99f62ceacf1746470082450e1 | function LN = lnbl (z, varargin)
% CONSTRUCT an lnbl
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
LN=mklnbl;
if nargin==0;
return
elseif nargin==1,
LN=nlmko... |
github | reklab/reklab_public-master | lnl2pc.m | .m | reklab_public-master/nlid_tools/@lnlbl/lnl2pc.m | 5,379 | utf_8 | 1ba59db8f8422c644ba2202843279603 | function pc_model = lnl2pc(lnl,hlen,numpaths,method);
% converts lnl into parallel cascde.
%
% syntax: pc_model = lnl2pc(lnl,hlen,numpaths,method);
%
% method can be 'kernels', 'kernel2','delays'
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the ... |
github | reklab/reklab_public-master | segdatDemo.m | .m | reklab_public-master/nlid_tools/nlid_demo/segdatDemo.m | 3,813 | utf_8 | 622341351785f0febd3b0e7880c055a0 | function segdatDemo ()
% segdatDemo
% Demonstrate segdat and its functions
clear all
%% Generate a simple segdat oeject by concatonating two nldat objects with no overlap
S=segdat;
X=nldat(ones(1000,1),'domainIncr',.001,'chanNames',{'X'});
XS=segdat(X);
Y=nldat(ones(500,1)*2,'domainIncr',.001,'domainStart',2, 'chanN... |
github | reklab/reklab_public-master | nldatDemo.m | .m | reklab_public-master/nlid_tools/nlid_demo/nldatDemo.m | 1,174 | utf_8 | be341f3611ea9ab78a70f63674755164 | nfunction nldatDemo( X )
% nldatDemo - demonstrate various methods for nldat.
% Detailed explanation goes here
figure(1); clf
x=randn(1000,1);
X=nldat(x, 'comment','Test comment');
set (X,'domainIncr',.001,'chanNames',{'One'}, 'chanUnits',{'Volts'});
set(X,'domainName','Time','domainStart',0);
plot (X);
plot (cho... |
github | reklab/reklab_public-master | nlid_demo.m | .m | reklab_public-master/nlid_tools/nlid_demo/nlid_demo.m | 3,214 | utf_8 | d30c2f69dd56f3c6426e88991428846f | function nlid_demo (model_type, x, noise_level);
% NLID_DEMO - Demonstrate Object Oriented NLID identification
% xin - input signal
% model_type - type of model to simulate; see nlid_sim for valid options;
% default value is 'LN2';
%
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of ... |
github | reklab/reklab_public-master | linearID_Demo.m | .m | reklab_public-master/nlid_tools/nlid_demo/linearID_Demo.m | 5,047 | utf_8 | 84fc094e31599a2a4ffda416f7f8bf8a | function irfDemo (inputCutOff, noiseLevel, nLags,nFFT, nSamp, sysType)
% mod9Demo (inputCutOff, noiseLevel, nLags, nSamp)
% Demonstrate IRF estimation for various systems
% inputCutOff - normalized cutoff for input singal (0-1)
% noiseLevel - ration of noise STD to output SRD (0 -100);
% nLags - lenght of IRF
% nSamp ... |
github | reklab/reklab_public-master | setdef.m | .m | reklab_public-master/nlid_tools/@param/setdef.m | 819 | utf_8 | 80e40d30b75e62ab7f0c9618e61d1638 | function Pout = setdefault (Pin, varargin );
% set the default value for elements within a parameter set
% Pin - input paramter array
% varagin - name/value pairs to set
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details... |
github | reklab/reklab_public-master | setdefault.m | .m | reklab_public-master/nlid_tools/@param/setdefault.m | 819 | utf_8 | 80e40d30b75e62ab7f0c9618e61d1638 | function Pout = setdefault (Pin, varargin );
% set the default value for elements within a parameter set
% Pin - input paramter array
% varagin - name/value pairs to set
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details... |
github | reklab/reklab_public-master | kern.m | .m | reklab_public-master/nlid_tools/@kern/kern.m | 5,650 | utf_8 | 2fc8c447b45be051a40ca45c5eb6dadd | classdef kern < nldat
% kern - kernel class for NLID toolbox
% Parent: nldat
properties
parameterSet
end
methods
function K = kern (x,varargin)
K.parameterSet=param('paramName','nLags','paramDefault',16, ...
'paramHelp','Number... |
github | reklab/reklab_public-master | nlident.m | .m | reklab_public-master/nlid_tools/@wseries/nlident.m | 3,770 | utf_8 | 3c22d4b1223c987bdac6387b585f18d4 | function ws = nlident (ws, z, varargin)
% Identify a series (wiener series object)
% Copyright 1999-2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
if nargin > 2
set(ws,vara... |
github | reklab/reklab_public-master | ws2vs.m | .m | reklab_public-master/nlid_tools/@wseries/ws2vs.m | 1,931 | utf_8 | ddd2c1900380ab0084ec0ca7579e9ce6 | function vs = ws2vs(ws,vsin);
% converts a wiener series into a volterra series
% uses theorem 5.3 from Rugh (1981).
% Copyright 1999-2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.t... |
github | reklab/reklab_public-master | vkern.m | .m | reklab_public-master/nlid_tools/@vkern/old/vkern.m | 514 | utf_8 | 8b9e3b2cbcccc225d9e7e4db7005b831 | function VK = wvkern (z, varargin)
% Volterra kernel object
% Parent: kern
% Copyright 1999-2003, Robert E Kearney
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
VK=mkvkern;
if nargin==0;
return
elseif nargin==1,
V... |
github | reklab/reklab_public-master | nlm2vs.m | .m | reklab_public-master/nlid_tools/@nlm/nlm2vs.m | 6,433 | utf_8 | 2fe9a95644d18a73914b3893d5a86480 | function vs = nlm2vs(nlmodel, vsin)
% generate Volterra kernels for a NLM model
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see copying.txt and gpl.txt
subsys = get(nlmodel,'elements');
[nparal... |
github | reklab/reklab_public-master | lnl2vs.m | .m | reklab_public-master/nlid_tools/@vseries/lnl2vs.m | 2,799 | utf_8 | ae21239582395a5a2176552c4e9e2ac5 | function VKernel = lnl2vs(lnl,hlen,order);
% computes Volterra kernels of a lnl cascade.
%
% syntax VKernel = lnl2volt(lnl,hlen,order);
warning ('iunder development');
elements = get(lnl,'elements');
Ts = get(lnl,'Ts');
g = get(elements{1},'Kernel');
m = elements{2};
mc = polynom(m,'polyType','power');
coeffs = get... |
github | reklab/reklab_public-master | hessian.m | .m | reklab_public-master/nlid_tools/@vseries/hessian.m | 1,395 | utf_8 | a9dd3832cbd8bf9bc086094c7915dde2 | function H = hessian(vs,z,varargin);
% computes hessian for least squares estimate of a volterra series
% make sure that the second argumment is either nldat or double,
% and contains enough colums for input(s) and output
if ~(isa (z,'double') | isa(z,'nldat'))
error (' Second argument must be of class double, or ... |
github | reklab/reklab_public-master | vs2ws.m | .m | reklab_public-master/nlid_tools/@vseries/vs2ws.m | 1,919 | utf_8 | 4ddc949f174933a7ca232dbf737bb217 | function ws = vs2ws(vs,wsin);
% converts a wiener series into a volterra series
% uses theorem 5.4 from Rugh (1981).
% Copyright 2003, Robert E Kearney and David T Westwick
% This file is part of the nlid toolbox, and is released under the GNU
% General Public License For details, see ../copying.txt and ../gpl.txt
... |
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