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m losstest.m

% MATLAB function losstest.m checks out whether % or not a Q-port network is lossless. For that % purpose, the network's Q-by-Q scattering matrix, S, % must be specified. % Invocation of function
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html 414-419.html

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asv arsimulat.asv

function [v]=arsimulat(w,A,C,n,ndisc) %ARSIM Simulation of AR process. % % v=ARSIM(w,A,C,n) simulates n time steps of the AR(p) process % % v(k,:)' = w' + A1*v(k-1,:)' +...+ Ap*v(k-p,:)' + eta(k
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www.eeworm.com/read/341201/12103661

m arfit.m

function [w, A, C, sbc, fpe, th]=arfit(v, pmin, pmax, selector, no_const) %ARFIT Stepwise least squares estimation of multivariate AR model. % % [w,A,C,SBC,FPE,th]=ARFIT(v,pmin,pmax) produces estimat
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www.eeworm.com/read/341201/12103675

m adjph.m

function ox=adjph(x) %ADJPH Normalization of columns of a complex matrix. % % Given a complex matrix X, OX=ADJPH(X) returns the complex matrix OX % that is obtained from X by multiplying column vect
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m arsim.m

function [v]=arsim(w,A,C,n,ndisc) %ARSIM Simulation of AR process. % % v=ARSIM(w,A,C,n) simulates n time steps of the AR(p) process % % v(k,:)' = w' + A1*v(k-1,:)' +...+ Ap*v(k-p,:)' + eta(k,:)'
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m arsimulat.m

function [v]=arsimulat(w,A,C,n,ndisc) %ARSIM Simulation of AR process. % % v=ARSIM(w,A,C,n) simulates n time steps of the AR(p) process % % v(k,:)' = w' + A1*v(k-1,:)' +...+ Ap*v(k-p,:)' + eta(k
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www.eeworm.com/read/152398/12117699

m transform.m

function [T,M]=transform(A) % The function finds a transformation matrix T that transform % a matrix or cell array A (by column switching)to a matrix M % having all diagonal elements = 0 (M = A*
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inl linearequation.inl

//LinearEquation.inl 线性方程(组)求解函数(方法)定义 // Ver 1.0.0.0 // 版权所有(C) 何渝, 2002 // 最后修改: 2002.5.31 #ifndef _LINEAREQUATION_INL #define _LINEAREQUATION_INL //全选主元高斯消去法 template int L
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www.eeworm.com/read/152129/12138201

m classif.m

function classification = classif(Ytrain, Ytest) % classification = classify(Ytrain, Ytest) % % Given the train matrix Ytrain and the test matrix Ytest, % this function returs a vector classificat
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