An adaptive Gauss-Newton algorithm for training multilayer nonlinear filters that have embedded memory

We describe herein a new means of training dynamic multilayer nonlinear adaptive filters, orneural networks. We restrict our discussion to multilayer dynamic Volterra networks, which are structured so as to restrict their degrees of computational freedom, based on a priori knowledge about the dynami...

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Bibliographic Details
Published in:	Circuits, systems, and signal processing Vol. 18; no. 4; pp. 407 - 429
Main Authors:	Rabinowitz, M., Gutt, G. M., Franklin, G. F.
Format:	Journal Article
Language:	English
Published:	Heidelberg Springer 01.01.1999 Springer Nature B.V
Subjects:	Adaptive filters Algorithms Applied sciences Circuit properties Dynamical systems Electric, optical and optoelectronic circuits Electronic circuits Electronics Exact sciences and technology Frequency filters Multilayers Networks Nonlinear dynamics Nonlinearity Training Waveform Adaptive algorithm Non linear filter Gauss Newton method Optimization method Block diagram Modeling Experimental result Multimachine power system Volterra series Algorithm performance Finite impulse response filter Cost function
ISSN:	0278-081X, 1531-5878
Online Access:	Get full text
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