代码搜索：gradient

找到约 2,951 项符合「gradient」的源代码

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m demgpot.m

function g = demgpot(x, mix) %DEMGPOT Computes the gradient of the negative log likelihood for a mixture model. % % Description % This function computes the gradient of the negative log of the % uncon
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www.eeworm.com/read/253950/12173340

m gradchek.m

function [gradient, delta] = gradchek(w, func, grad, varargin) %GRADCHEK Checks a user-defined gradient function using finite differences. % % Description % This function is intended as a utility for
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www.eeworm.com/read/253950/12173601

m gbayes.m

function [g, gdata, gprior] = gbayes(net, gdata) %GBAYES Evaluate gradient of Bayesian error function for network. % % Description % G = GBAYES(NET, GDATA) takes a network data structure NET together
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www.eeworm.com/read/253950/12173919

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/253950/12174101

htm gradchek.htm

Netlab Reference Manual gradchek gradchek Purpose Checks a user-defined gradient function using finite differences. Synopsi
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htm netgrad.htm

Netlab Reference Manual netgrad netgrad Purpose Evaluate network error gradient for generic optimizers Synopsis
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m rbfgrad.m

function [g, gdata, gprior] = rbfgrad(net, x, t) %RBFGRAD Evaluate gradient of error function for RBF network. % % Description % G = RBFGRAD(NET, X, T) takes a network data structure NET together % wi
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www.eeworm.com/read/339665/12211210

m demgpot.m

function g = demgpot(x, mix) %DEMGPOT Computes the gradient of the negative log likelihood for a mixture model. % % Description % This function computes the gradient of the negative log of the % uncon
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www.eeworm.com/read/339665/12211240

m gradchek.m

function [gradient, delta] = gradchek(w, func, grad, varargin) %GRADCHEK Checks a user-defined gradient function using finite differences. % % Description % This function is intended as a utility for
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www.eeworm.com/read/339665/12211601

m gbayes.m

function [g, gdata, gprior] = gbayes(net, gdata) %GBAYES Evaluate gradient of Bayesian error function for network. % % Description % G = GBAYES(NET, GDATA) takes a network data structure NET together
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