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/147529/5728646
m fminusub.m
function [x,FVAL,GRADIENT,HESSIAN,EXITFLAG,OUTPUT] = fminusub(funfcn,x,verbosity,options,Fval,Gval,Hval,varargin)
%FMINUSUB Finds the minimum of a function of several variables.
% Copyright (c)
www.eeworm.com/read/147529/5728856
m fminusub.m
function [x,FVAL,GRADIENT,HESSIAN,EXITFLAG,OUTPUT] = fminusub(funfcn,x,verbosity,options,Fval,Gval,Hval,varargin)
%FMINUSUB Finds the minimum of a function of several variables.
% Copyright (c)
www.eeworm.com/read/359185/6352564
m backpropagation_cgd.m
function [D, Wh, Wo] = Backpropagation_CGD(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm and conjugate gradient descent
www.eeworm.com/read/493206/6398574
m backpropagation_cgd.m
function [D, Wh, Wo] = Backpropagation_CGD(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm and conjugate gradient descent
www.eeworm.com/read/478412/6717475
m onion.m
function Status = Onion(Surface, Layers, T1, T2)
% Onion - Splits a lens into a number of layers for the purpose of analysing the effect of an axial
% temperature gradient.
%
% Usage : Status = On
www.eeworm.com/read/410924/11265010
m backpropagation_cgd.m
function [D, Wh, Wo] = Backpropagation_CGD(train_features, train_targets, params, region)
% Classify using a backpropagation network with a batch learning algorithm and conjugate gradient descent
www.eeworm.com/read/263879/11338170
m fminusub.m
function [x,FVAL,GRADIENT,HESSIAN,EXITFLAG,OUTPUT] = fminusub(funfcn,x,verbosity,options,Fval,Gval,Hval,varargin)
%FMINUSUB Finds the minimum of a function of several variables.
% Copyright (c)
www.eeworm.com/read/337307/12377455
m fminusub.m
function [x,FVAL,GRADIENT,HESSIAN,EXITFLAG,OUTPUT] = fminusub(funfcn,x,verbosity,options,Fval,Gval,Hval,varargin)
%FMINUSUB Finds the minimum of a function of several variables.
% Copyright (c)