Growing filters for finite impulse response networks
M. Diepenhorst, Jos A. G. Nijhuis, R.S. Venema, Lambert Spaanenburg · 2002
Time-delay neural networks are well-suited for prediction purposes. A particular implementation is the finite impulse response (FIR) neural net. A major design problem exists in establishing the optimal order of such filters while minimizing the number of weights. Here, a constructive solution inspired by cascade learning is outlined and illustrated by some typical case-studies.