Лабораторные работы / lab3 / lab3log

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>> [alphabet,targets] = prprob;
>> [R,Q]= size(alphabet);
>> [S2,Q] = size(targets);
>> S1 = 10;
>> net = newff (minmax (alphabet), [S1 S2], {'logsig' 'logsig'}, 'traingdx');
Warning: NEWFF used in an obsolete way.
> In obs_use at 18
In newff>create_network at 127
In newff at 102
See help for NEWFF to update calls to the new argument list.

>> net.LW{2,1}= net.LW{2,1}*0.01;
>> net.b{2}=net.b{2}*0.01;
>> net = newff (minmax (alphabet), [S1 S2], {'logsig' 'logsig'}, 'traingdx'); net.LW{2,1}= net.LW{2,1}*0.01; net.b{2}=net.b{2}*0.01;
Warning: NEWFF used in an obsolete way.
> In obs_use at 18
In newff>create_network at 127
In newff at 102
See help for NEWFF to update calls to the new argument list.

>> P = alphabet;
>> T = targets;
>> net.performFcn = 'sse';
>> net.trainParam.goal = 0.1;
>> net.trainParam.show = 20;
>> net.trainParam.epochs = 5000;
>> net.trainParam.mc = 0.95;
>> [net,tr] = train(net, P, T);
>> [net,tr] = train(net, P, T);
>> netn = net;
>> netn.trainParam.goal = 0.6;
>> netn.trainParam.epochs = 500;
>> [netn,tr] = train(netn, P, T);
>> A = alphabet(:,1)+randn(35,1)*0.2;
>> W = alphabet(:,23)+randn(35,1)*0.2;
>> TestA = sim(netn,A)

TestA =

0.7252
0.0003
0.0003
0.0157
0.0416
0.0018
0.0108
0.0327
0.0183
0.0007
0.0966
0.0410
0.0228
0.1386
0.0014
0.0002
0.0240
0.0227
0.0079
0.0028
0.0008
0.0051
0.1994
0.0127
0.0282
0.0119

>> TestW = sim(netn,W)

TestW =

0.0276
0.0004
0.0007
0.0134
0.0092
0.0005
0.0118
0.0386
0.0021
0.0006
0.1011
0.0972
0.0317
0.1369
0.0137
0.0001
0.0709
0.0150
0.0063
0.0031
0.0068
0.0149
0.6949
0.0014
0.0011
0.0001

>>