Description: TRAINDIFFEVOL(NET,Pd,Tl,Ai,Q,TS,VV) takes these inputs,
NET - Neural network.
Pd - Delayed input vectors.
Tl - Layer target vectors.
Ai - Initial input delay conditions.
Q - Batch size.
TS - Time steps.
VV - Either empty matrix [] or structure of validation vectors.
and returns,
NET - Trained network.
TR - Training record of various values over each epoch:
TR.epoch - Epoch number.
TR.perf - Training performance.
TR.vperf - Validation performance.
TR.tperf - Test performance.
TR.mu - Adaptive mu value.
To Search:
File list (Check if you may need any files):
traindiffevol.m
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