Noise suppress exponential growth for hybrid Hopfield neural networks

Song Zhu, Yi Shen and Guici Chen

Mathematics and Computers in Simulation (MATCOM), 2012, vol. 86, issue C, 10-20

Abstract: In this paper, we show that noise can transform a hybrid neural networks, whose solution may grow exponentially, into a new stochastic one, whose solution grows at most polynomially. In other words, we reveal that noise can suppress the exponential growth in hybrid Hopfield neural networks.

Keywords: Exponential growth; Polynomial growth; Generalized Itô formula; Markov chain (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:86:y:2012:i:c:p:10-20

DOI: 10.1016/j.matcom.2010.11.014

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