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Download fileGlobal asymptotic convergence of nonlinear relaxation equations realised through a recurrent perceptron
conference contribution
posted on 2010-01-18, 13:51 authored by Danilo P. Mandic, Jonathon ChambersConditions 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
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