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Title: Global asymptotic convergence of nonlinear relaxation equations realised through a recurrent perceptron
Authors: Mandic, Danilo P.
Chambers, Jonathon
Issue Date: 1999
Publisher: © IEEE
Citation: MANDIC, D.P. and CHAMBERS, J., 1999. Global asymptotic convergence of nonlinear relaxation equations realised through a recurrent perceptron. IN: Proceedings of the 1999 IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP '99, Phoenix, Arizona, 15th-19th March 1999, Vol. 2, pp. 1037-1040
Abstract: Conditions for global asymptotic stability (GAS) of a nonlinear relaxation equation realised by a nonlinear autoregressive moving average (NARMA) recurrent perceptron are provided. Convergence is derived through fixed point iteration (FPI) techniques, based upon a contraction mapping feature of a nonlinear activation function of a neuron. Furthermore, nesting is shown to be a spatial interpretation of an FPI, which underpins a pipelined recurrent neural network (PRNN) for nonlinear signal processing
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ICASSP.1999.759885
URI: https://dspace.lboro.ac.uk/2134/5813
ISBN: 0780350413
Appears in Collections:Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)

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