代码搜索：Recurrent
找到约 100 项符合「Recurrent」的源代码
代码结果 100
www.eeworm.com/read/349415/10828273
help recurrent2.help
"recurren2.cpp" Help File
The purpose is to test a
recurrent networks ability to
learn the XOR function and to
function on a KOHEN_SOFM function
and learning rule, as opposed to
the convention
www.eeworm.com/read/349415/10828281
cpp recurrent2.cpp
/*
nn-utility (Provides neural networking utilities for c++ programmers)
Copyright (C) 2003 Panayiotis Thomakos
This library is free software; you can redistribute it and/or
modi
www.eeworm.com/read/399996/7817026
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/397099/8069036
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/245941/12771140
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/330850/12865135
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/317622/13500949
m backpropagation_recurrent.m
function [test_targets, W, J] = Backpropagation_Recurrent(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation recurrent network with a batch learning algorithm
www.eeworm.com/read/316604/13520513
m backpropagation_recurrent.m
function [D, Wh, Wo] = Backpropagation_Recurrent(train_features, train_targets, params, region)
% Classify using a backpropagation recurrent network with a batch learning algorithm
% Inputs:
% f
www.eeworm.com/read/359185/6352580
m backpropagation_recurrent.m
function [D, Wh, Wo] = Backpropagation_Recurrent(train_features, train_targets, params, region)
% Classify using a backpropagation recurrent network with a batch learning algorithm
% Inputs:
% f
www.eeworm.com/read/493206/6398590
m backpropagation_recurrent.m
function [D, Wh, Wo] = Backpropagation_Recurrent(train_features, train_targets, params, region)
% Classify using a backpropagation recurrent network with a batch learning algorithm
% Inputs:
% f