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/455033/7378519
edp mortar-dn-4.edp
assert(version>=2.23);
// Mortar (4 sub domain)
// with matrix -et Precon Conjugade Gradient --
// Neuman -> Dirichlet .
// -------------------------------
func f=1+x+y;
real g=1;
int withp
www.eeworm.com/read/197958/7960681
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/397477/8043455
m modkurt.m
function [chm, snrk] = modkurt(ch,k,p);
% Modify the kurtosis in one step, by moving in gradient direction until
% reaching the desired kurtosis value.
% It does not affect the mean nor the variance
www.eeworm.com/read/196814/8058701
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/244945/12829489
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/329331/12960463
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/140851/13058955
m demolgd1.m
%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampli
www.eeworm.com/read/138798/13211959
m demolgd1.m
%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampli
www.eeworm.com/read/137285/13335136
c first.c
/* first.c
The first ansi program I have written.
It will do conjugate gradients on a function
which has arguments
and which has a gradient routine
that has arguments
too */
#inclu
www.eeworm.com/read/316604/13520497
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