EURASIP Journal on Applied Signal Processing 2003:12, 1229–1237 c 2003 Hindawi Publishing

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EURASIP Journal on Applied Signal Processing 2003:12, 1229–1237 c 2003 Hindawi Publishing Corporation Nonlinear System Identiﬁcation Using Neural Networks Trained with Natural Gradient Descent Mohamed Ibnkahla Electrical and Computer Engineering Department, Queen’s University, Kingston, Ontario, Canada K7L 3N6 Email: mohamed.ibnkahla@ece.queensu.ca Received 13 December 2002 and in revised form 17 May 2003 We use natural gradient (NG) learning neural networks (NNs) for modeling and identifying nonlinear systems with memory. The nonlinear system is comprised of a discrete-time linear ﬁlter H followed by a zero-memory nonlinearity g(·). The NN model is composed of a linear adaptive ﬁlter Q followed by a two-layer memoryless nonlinear NN....

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