www.gusucode.com > nnet 工具箱 matlab 源码程序 > nnet/nnnetfun/noloop.m
function net = noloop(net) %NOLOOP Remove neural network open and closed feedback loops. % % <a href="matlab:doc noloop">noloop</a>(NET) takes a network and transforms any outputs marked % as open or closed loop (i.e. NET.<a href="matlab:doc nnproperty.net_outputs">outputs</a>{i}.<a href="matlab:doc nnproperty.output_feedbackMode">feedbackMode</a> = 'open' or % 'closed') to no loop (i.e. ''). % % Here a NARX network is designed. The NARX network has a standard input % and an open loop feedback output to an associated feedback input. % % [X,T] = <a href="matlab:doc simplenarx_dataset">simplenarx_dataset</a>; % net = <a href="matlab:doc narxnet">narxnet</a>(1:2,1:2,10); % [Xs,Xi,Ai,Ts] = <a href="matlab:doc preparets">preparets</a>(net,X,{},T); % net = <a href="matlab:doc train">train</a>(net,Xs,Ts,Xi,Ai); % <a href="matlab:doc view">view</a>(net) % Y = net(Xs,Xi,Ai) % % Now the network is converted to no loop form. The output and second % input are no longer associated. % % net = <a href="matlab:doc noloop">noloop</a>(net); % <a href="matlab:doc view">view</a>(net) % [Xs,Xi,Ai,Ts] = <a href="matlab:doc preparets">preparets</a>(net,X,T); % Y = net(Xs,Xi,Ai) % % See also OPENLOOP, CLOSEDLOOP. % Copyright 2010 The MathWorks, Inc. for i=find(net.outputConnect) if ~isempty(net.outputs{i}.feedbackMode) net.outputs{i}.feedbackMode = ''; end end