代码搜索：Gradient
找到约 2,951 项符合「Gradient」的源代码
代码结果 2,951
www.eeworm.com/read/179143/9369346
m gazbgradeval.m
function [nsol, val] = gaZBGradEval(sol,options)
% This evaluation function takes in a potential solution and two options
% options(3) is the percent of time to perform the gradient heuristic to the
www.eeworm.com/read/374775/9385076
m gazbgradeval.m
function [nsol, val] = gaZBGradEval(sol,options)
% This evaluation function takes in a potential solution and two options
% options(3) is the percent of time to perform the gradient heuristic to the
www.eeworm.com/read/177674/9442395
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
www.eeworm.com/read/177674/9442403
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
www.eeworm.com/read/177674/9442556
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
www.eeworm.com/read/177674/9442676
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
www.eeworm.com/read/176823/9483099
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
www.eeworm.com/read/176823/9483110
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
www.eeworm.com/read/176823/9483237
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
www.eeworm.com/read/176823/9483368
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