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找到约 10,000 项符合「Matrix」的源代码

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m makeay.m

function [Ay, by] = makeAy(baseMVA, ng, gencost, pgbas, qgbas, ybas) % makeAy: Make the A matrix and RHS for the CCV formulation. % % [Ay, by] = makeAy(baseMVA, ng, gencost, pgbas, qgbas, ybas) con
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m myhilb.m

function[A,B]=myhilb(n,m) % MYHILB 生成一个Hilbert矩阵 % [A,B]=myhilb(n,m) % where % n,m are size of the Hilbert matrix,if only one % argument given,then a square matrix is generated % A is the Hil
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m myhilb1.m

function[A,B]=myhilb(n,m) %问题：生成一个Hilbert矩阵，该矩阵是一个n×m矩阵，它的第i行 %第j列的元素为1/(i+j-1)。如果想在编写的函数中实现下面几点： %1）如果只给出一个输入参数，则会自动生成一个方阵，即有m=n %2）如果想返回两个参数A和B，则返回的B矩阵为A矩阵的平方， % 即B=A'A %3)在函数中给出合适的帮助信息，包括基本 ...
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www.eeworm.com/read/324303/13273688

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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h mx_solve.h

// Copyright (C) 2003 Zbigniew Leyk (zbigniew.leyk@anu.edu.au) // and David E. Stewart (david.stewart@anu.edu.au) // and Ronan Collobert (collober@idiap.ch) //
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m anal1.m

function [E,Nc,mCe,mC,T] = anal1(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 Mi
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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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java eigenvaluedecomposition.java

package Jama; import Jama.util.*; /** Eigenvalues and eigenvectors of a real matrix. If A is symmetric, then A = V*D*V' where the eigenvalue matrix D is diagonal and the eigenvecto
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www.eeworm.com/read/137160/13342256

m nbayesc.m

%NBAYESC Bayes Classifier for given normal densities % % W = NBAYESC(U,G) % % INPUT % U Dataset of means of classes % G Covariance matrices (optional; default: identity matrices) % % OUTP
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