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m distance_kld_symmetric.m

function K = distance_KLD_symmetric(v, P, Q) %function K = distance_KLD_symmetric(v, P, Q) % % INPUTS: % v - difference between two means v = p - q % P, Q - covariance matrices % % OUTPUT:
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www.eeworm.com/read/233414/14154614

html mod2dense.html

Dense Modulo-2 Matrix Routines Dense Modulo-2 Matrix Routines This module implements operations on matrices in which the elements are all
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www.eeworm.com/read/228652/14371662

m size.m

function [n1,n2] = size(P,dim) % SIZE -- size of coefficient matrices of matrix polynomial % % n = size(P) % [n1,n2] = size(P) % n = size(P,dim) % % The effec
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www.eeworm.com/read/218613/14912783

m mkron.m

%mkron Kronecker (tensor) product of several matrices. % That is, mkron(X,Y,Z)=kron(kron(X,Y),Z). % Copyright (C) 2005 Geza Toth E.mail: toth@alumni.nd.edu % % This program is free software;
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www.eeworm.com/read/217040/14981369

dat matrx1.dat

MATRICES FOR INPUT TO TEST ROUTINES Size of matrix (NxN), Number of solutions: 3 2 Matrix A: 1.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 3.0 Solution vectors: 1.0 0.0 0.0 1.0 1.0 1.0 NEXT PROBLEM Size
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www.eeworm.com/read/216463/15006055

html mod2dense.html

Dense Modulo-2 Matrix Routines Dense Modulo-2 Matrix Routines This module implements operations on matrices in which the elements are all
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www.eeworm.com/read/15127/432470

dat matrx1.dat

MATRICES FOR INPUT TO TEST ROUTINES Size of matrix (NxN), Number of solutions: 3 2 Matrix A: 1.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 3.0 Solution vectors: 1.0 0.0 0.0 1.0 1.0 1.0 NEXT PROBLEM Size
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www.eeworm.com/read/475809/1381144

dat matrx1.dat

MATRICES FOR INPUT TO TEST ROUTINES Size of matrix (NxN), Number of solutions: 3 2 Matrix A: 1.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 3.0 Solution vectors: 1.0 0.0 0.0 1.0 1.0 1.0 NEXT PROBLEM Size
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www.eeworm.com/read/475809/1381765

dat matrx1.dat

MATRICES FOR INPUT TO TEST ROUTINES Size of matrix (NxN), Number of solutions: 3 2 Matrix A: 1.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 3.0 Solution vectors: 1.0 0.0 0.0 1.0 1.0 1.0 NEXT PROBLEM Size
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www.eeworm.com/read/251838/4415376

m dbn_to_hmm.m

function [prior, transmat] = dbn_to_hmm(bnet) % DBN_TO_HMM Compute the discrete HMM matrices from a simple DBN % [prior, transmat] = dbn_to_hmm(bnet) onodes = bnet.observed; ss = length(bnet.intra);
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