Adaptive training of feedback neural networks for non-linear filtering

The authors propose a general framework which encompasses the training of neural networks and the adaptation of filters. It is shown that neural networks can be considered as general nonlinear filters which can be trained adaptively, i.e., which can undergo continual training. A unified view of gradient-based training algorithms for feedback networks is proposed, which gives rise to new algorithms. The use of some of these algorithms is illustrated by examples of nonlinear adaptive filtering and process identification.<<ETX>>

[1]  P. Feintuch.  An adaptive recursive LMS filter , 1976, Proceedings of the IEEE.

[2]  C. Richard Johnson,et al.  On adaptive IIR filters and parallel adaptive identifiers with adaptive error filtering , 1981, ICASSP.

[3]  P. Kumar,et al.  Theory and practice of recursive identification , 1985, IEEE Transactions on Automatic Control.

[4]  K. H. Barratt.  Digital Coding of Waveforms , 1985 .

[5]  Peter No,et al.  Digital Coding of Waveforms , 1986 .

[6]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[7]  Jerry D. Gibson,et al.  Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.

[8]  Ronald J. Williams,et al.  A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.

[9]  Sheng Chen,et al.  Representations of non-linear systems: the NARMAX model , 1989 .

[10]  J. Shynk.  Adaptive IIR filtering , 1989, IEEE ASSP Magazine.

[11]  Jing Peng,et al.  An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories , 1990, Neural Computation.

[12]  Michael I. Jordan.  Attractor dynamics and parallelism in a connectionist sequential machine , 1990 .

[13]  2 - Réseaux de neurones pour le filtrage non linéaire adaptatif , 1991 .

[14]  Sylvie Marcos,et al.  Analysis of gradient-based adaptation algorithms for linear and nonlinear recursive filters , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[15]  Pierre Roussel-Ragot,et al.  Neural Networks and Nonlinear Adaptive Filtering: Unifying Concepts and New Algorithms , 1993, Neural Computation.