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/333606/12668944
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/333314/12688065
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/246557/12719753
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/145119/12753153
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/143706/12849516
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/143706/12849538
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/143706/12849819
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/143706/12849994
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/244471/12861398
m gvf.m
function [u,v] = GVF(f, mu, ITER)
%GVF Compute gradient vector flow.
% [u,v] = GVF(f, mu, ITER) computes the
% GVF of an edge map f. mu is the GVF regularization coefficient
% and ITER is t
www.eeworm.com/read/242897/12974211
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