代码搜索：NetWork
找到约 10,000 项符合「NetWork」的源代码
代码结果 10,000
www.eeworm.com/read/414991/11086880
m demopsonet.m
% demoPSOnet.m
% script to show a quick, uncomplicated demo of using trainpso for training
% a neural net
%
% tries to build a feedforward neural net to approximate a noisy increaing
% sin funct
www.eeworm.com/read/414357/11119282
m nnfexist.m
function ok = nnfexist(d)
%NNFEXIST Neural Network Design utility function.
% Copyright 1994-2002 PWS Publishing Company and The MathWorks, Inc.
% $Revision: 1.6 $
% First Version, 8-31-95.
www.eeworm.com/read/268726/11124525
txt contact.txt
与 MCAFEE 和 NETWORK ASSOCIATES 联系
最新更新时间：2003 年 2 月 12 日
最好使用 Courier 字体查看本文件，才能正常显示
各种语言中的特殊字符。
_______________________________________________
目录
- 技术支持
- 客户服务
-
www.eeworm.com/read/413912/11137090
m mdnpak.m
function w = mdnpak(net)
%MDNPAK Combines weights and biases into one weights vector.
%
% Description
% W = MDNPAK(NET) takes a mixture density network data structure NET
% and combines the network w
www.eeworm.com/read/413912/11137092
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 sampling X
www.eeworm.com/read/413912/11137192
m nethess.m
function [h, varargout] = nethess(w, net, x, t, varargin)
%NETHESS Evaluate network Hessian
%
% Description
%
% H = NETHESS(W, NET, X, T) takes a weight vector W and a network data
% structure NET, to
www.eeworm.com/read/413912/11137266
m mlpfwd.m
function [y, z, a] = mlpfwd(net, x)
%MLPFWD Forward propagation through 2-layer network.
%
% Description
% Y = MLPFWD(NET, X) takes a network data structure NET together with a
% matrix X of input vec
www.eeworm.com/read/413912/11137293
m mdn.m
function net = mdn(nin, nhidden, ncentres, dim_target, mix_type, ...
prior, beta)
%MDN Creates a Mixture Density Network with specified architecture.
%
% Description
% NET = MDN(NIN, NHIDDEN, NCENTRE
www.eeworm.com/read/413912/11137294
m rbfpak.m
function w = rbfpak(net)
%RBFPAK Combines all the parameters in an RBF network into one weights vector.
%
% Description
% W = RBFPAK(NET) takes a network data structure NET and combines the
% componen