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m anal3.m

function [E,Nc,mC,T] = anal3(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
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m analysis.m

function [E,bE,Nc,mCe,mC,T,U] = analysis(M,D,st,s); % % Ph.D. Thesis % Copyright by Leandro Nunes de Castro % March, 2000 % Immune Network (iNet) - Description in iNet.doc % Function determine
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m contents.m

% MCMC -- Markov Chain Monte Carlo Tools % Copyright (c) 1998, Harvard University. Full copyright in the file Copyright % % There are three parts to this library of routines. % 1. *[rnd,pdf,lpr].m - d
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texi eigen.texi

@cindex eigenvalues and eigenvectors This chapter describes functions for computing eigenvalues and eigenvectors of matrices. There are routines for real symmetric and complex hermitian matrices,
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readme

The Linear Algebra with Applications Toolbox by Gareth Williams and Lisa Coulter Gareth Williams, box 8345, Stetson University, DeLand, FL 32720. williams@bliss.stetson.edu Lisa Coulte
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m gjinfo.m

function gjinfo %GJINFO %Computes reduced echelon form of random nx(n+1) matrix. %Uses Gauss Jordan elimination. %Finds time (in secs), # adds and mults. %Option of rational number format for m
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m uptrbk.m

function X = uptrbk(A,B) %Input - A is an N x N nonsingular matrix % - B is an N x 1 matrix %Output - X is an N x 1 matrix containing the solution to AX=B. % NUMERICAL METHODS: Matlab Program
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m lufact.m

function X = lufact(A,B) %Input - A is an N x N matrix % - B is an N x 1 matrix %Output - X is an N x 1 matrix containing the solution to AX = B. % NUMERICAL METHODS: Matlab Programs % (c) 200
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m latentlssvm.m

function [zt,model] = latentlssvm(varargin) % Calculate the latent variables of the LS-SVM classifier at the given test data % % >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
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m latentlssvm.m

function [zt,model] = latentlssvm(varargin) % Calculate the latent variables of the LS-SVM classifier at the given test data % % >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
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