代码搜索：NetWork
找到约 10,000 项符合「NetWork」的源代码
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www.eeworm.com/read/198191/7947787
m ff2.m
%QUESTION NO:3
% b)Design and Train a feedforward network for the following problem:
% Encoding: Consider an 8-input and 8-output problem, where the output
% should be equal to the input for
www.eeworm.com/read/298532/7951961
plg transfer.plg
Build Log
--------------------Configuration: Transfer - Win32 Debug--------------------
Command Lines
Creating command line "rc.exe /l 0x804 /f
www.eeworm.com/read/198041/7955700
h edpaddr.h
/*! \file edpaddr.h \brief Emerald Satellite EDP/I2C Bus Addresses. */
//*****************************************************************************
//
// File Name : 'edpaddr.h'
// Title : Eme
www.eeworm.com/read/197984/7958609
h bpnet.h
// BPNet.h: interface for the BPNet class.
//
// Copyright Gideon Pertzov, 2003
//
// This software is provided "as is" without express or implied
// warranties. You may freely copy and compile t
www.eeworm.com/read/398324/7994150
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/398324/7994268
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/398324/7994447
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/398324/7994604
m train.m
function net = train(net, tutor, varargin)
% TRAIN
%
% Train a max-win multi-class support vector classifier network using the
% specified tutor to train each component two-class network.
%
www.eeworm.com/read/397761/8023266
m example33_test.m
%test the bp network
%==============
%==============
input=str2num(input);
output=purelin(W2*tansig(W1*input,B1),B2);
out=purelin(W2*tansig(W1*P,B1),B2);
figure('color',[0.8 0.8 0.8],'positi