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m gaussian_prob.m

function p = gaussian_prob(x, m, C, use_log) % GAUSSIAN_PROB Evaluate a multivariate Gaussian density. % p = gaussian_prob(X, m, C) % p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
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www.eeworm.com/read/411667/11234364

m gaussian_prob.m

function p = gaussian_prob(x, m, C, use_log) % GAUSSIAN_PROB Evaluate a multivariate Gaussian density. % p = gaussian_prob(X, m, C) % p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
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www.eeworm.com/read/147186/12578559

m gaussian_prob.m

function p = gaussian_prob(x, m, C, use_log) % GAUSSIAN_PROB Evaluate a multivariate Gaussian density. % p = gaussian_prob(X, m, C) % p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
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www.eeworm.com/read/390322/8471229

m lec20mldemo1.m

% MIT 18.335 - Lecture 20 MATLAB Demo 1 % Conjugate Gradient % Per-Olof Persson, November 21, 2006 % Create 2-by-2 linear system A=[3,1; 1,2]; x0=[2;-2]; b=A*x0; % Evaluate and plot contour
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htm gpgrad.htm

Netlab Reference Manual gpgrad gpgrad Purpose Evaluate error gradient for Gaussian Process. Synopsis g = gpgrad
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www.eeworm.com/read/429878/8783868

htm errbayes.htm

Netlab Reference Manual errbayes errbayes Purpose Evaluate Bayesian error function for network. Synopsis e = er
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www.eeworm.com/read/429878/8783904

htm gbayes.htm

Netlab Reference Manual gbayes gbayes Purpose Evaluate gradient of Bayesian error function for network. Synopsis
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www.eeworm.com/read/429878/8783917

htm gperr.htm

Netlab Reference Manual gperr gperr Purpose Evaluate error function for Gaussian Process. Synopsis edata = gper
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www.eeworm.com/read/429878/8783943

htm rbfhess.htm

Netlab Reference Manual rbfhess rbfhess Purpose Evaluate the Hessian matrix for RBF network. Synopsis h = rbfhe
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www.eeworm.com/read/429878/8783999

htm rbfgrad.htm

Netlab Reference Manual rbfgrad rbfgrad Purpose Evaluate gradient of error function for RBF network. Synopsis
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