代码搜索：Statistical
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www.eeworm.com/read/150760/12264737
m stprpath.m
function stprpath(toolboxroot)
% STPRPATH sets path to Statistical Pattern Recognition Toolbox.
%
% Synopsis:
% stprpath
% stprpath(toolboxroot)
%
% Description:
% stprpath(toolboxroot) se
www.eeworm.com/read/150760/12266090
m contents.m
% Demos of the Statistical Pattern Recognition Toolbox.
%
% image_denoising - (dir) Image denoising using kernel PCA.
% ocr - (dir) Object Character Recognition.
%
% demo_anderson - G
www.eeworm.com/read/150760/12266152
m contents.m
% Linear feature extraction.
%
% lda - Linear Discriminant Analysis.
% pca - Principal Component Analysis.
% pcarec - Computes reconstructed vector after PCA projection.
%
% About: Statistic
www.eeworm.com/read/150760/12266161
m contents.m
% Fisher Linear Discriminat.
%
% fld - Fisher Linear Discriminat.
% fldqp - Fisher Linear Discriminat using quadratic programming.
%
% About: Statistical Pattern Recognition Toolbox
% (C) 1999-
www.eeworm.com/read/128468/14295322
m setaxis.m
function []=setaxis(handle,rect)
% function []=setaxis(handle,rect)
%
% SETAXIS sets scaling for the x- and y-axes
% on the plot with a given handle.
%
% See also AXIS.
%
% Statistical Patte
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txt readme.txt
% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 26.02.2000
% Modifi
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m contents.m
% Statistical learning methods.
%
% Included directories (implementing algorithms):
% minimax - (dir) Minimax learning algorithm.
% unsuper - (dir) Unsupervised learning methods, EM algori
www.eeworm.com/read/128468/14295464
m kmatrix.m
% KMATRIX computes kernel matrix for given data.
% [K] = kmatrix(X,ker,arg)
%
% Input:
% X [dim x N] data; dim - dimension; N number of data;
% ker [string] kernel identifier; options 'linear', 'rb
www.eeworm.com/read/128468/14295552
m chgnum.m
function [I]=chgnum(I,oldValue,newValue)
% [I]=chgnum(I,oldValue,newValue)
%
% CHGNUM chages oldValue(s) from the vector I to
% corresponding newValue(s) and returns the result.
% In other words it