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www.eeworm.com/read/137160/13342342
m distm.m
%DISTM Compute square Euclidean distance matrix
%
% D = DISTM(A,B)
%
% INPUT
% A,B Datasets or matrices; B is optional, default B = A
%
% OUTPUT
% D Square Euclidean distance dataset or
www.eeworm.com/read/137160/13342446
m setcost.m
%SETCOST Reset classification cost matrix of mapping
%
% W = SETCOST(W,COST,LABLIST)
%
% The classification cost matrix of the dataset W is reset to COST.
% W has to be a trained classifier. CO
www.eeworm.com/read/137160/13342659
m covm.m
%COVM Compute covariance matrix for large datasets
%
% C = COVM(A)
%
% Similar to C = COV(A) this routine computes the covariance matrix
% for the datavectors stored in the rows of A. No large int
www.eeworm.com/read/136972/13350466
cpp xt6-10.cpp
#include
using namespace std;
int main()
{void change(int *p);
int a[5][5],*p,i,j;
cout
www.eeworm.com/read/323118/13354402
readme
Directory
../Utilities
Contents
colSum.m
Sums the columns of matrices.
diagProduct.m
Fast way to get the diagonal of the product of two matrices.
dupCol.m
Creates a matrix
www.eeworm.com/read/136697/13365276
m corproen.m
function O=corproen(FAMbank,BeA,BdeA,L)
% O=corproen(FAMbank,BeA,BdeA,L)
%
% Correlation-Product Encoding. Kosko (1992)
%
% Correlation-product encoding :
% Defining pointwise the fuzzy Hebb matrix
www.eeworm.com/read/136697/13365429
m ptos_psc.m
function [FAMbank,msum,y2,m2e,m2u,M,mdens]=ptos_psc(esec,usec,samples,N,p,wii,wij,c,rands)
% [FAMbank,msum,y2,m2e,m2u,M,mdens]=ptos_psc(esec,usec,samples,N,p,wii,wij,c,rands)
%
% Product Space Cluste
www.eeworm.com/read/136697/13365488
m corminen.m
function O=corminen(FAMbank,BeA,BdeA,L)
% O=corminen(FAMbank,BeA,BdeA,L)
%
% Correlation-Minimum Encoding. Kosko (1992)
%
% Correlation-minimum encoding :
% Defining pointwise the fuzzy Hebb matrix
www.eeworm.com/read/321295/13409413
m anal2.m
function [E,Nc,mC,T] = anal2(M,D,st,s);
%
% Ph.D. Thesis
% Copyright by Leandro Nunes de Castro
% March, 2000
% Immune Network (iNet) - Description in iNet.doc
% Function determines the Minima
www.eeworm.com/read/321160/13411622
m ss_tbl31.m
Gold sequences for the table of problem 3.1 of Spread Spectrum Chapter
Note that the sequences are the columns of the below matrix not the rows,
so we have to take the transpose of the following matr