alexa Absolute stability of global pattern formation and parallel memory storage by competitive neural networks.
Engineering

Engineering

Journal of Information Technology & Software Engineering

Author(s): Cohen Michael A, Grossberg

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Discusses the process whereby input patterns are transformed and stored by competitive cellular networks, which arises in such diverse subjects as the short-term storage of visual or language patterns by neural networks, pattern formation due to the firing of morphogenetic gradients in developmental biology, control of choice behavior during macromolecular evolution, and the design of stable context-sensitive parallel processors. In addition to systems capable of approaching one of perhaps infinitely many equilibrium points in response to arbitrary input patterns and initial data, one finds in these subjects a wide variety of other behaviors, notably traveling waves, standing waves, resonance, and chaos. The questions of whether global pattern formation occurs and whether the global pattern formation property persists when system parameters slowly change in an unpredictable fashion due to self-organization (development and learning) are discussed. Model systems that exhibit the absolute stability property are examined, and it is shown that the use of fast symmetric competitive feedback is a robust design constraint for guaranteeing absolute stability of global pattern formation. (37 ref) (PsycINFO Database Record (c) 2016 APA, all rights reserved)

This article was published in IEEE Transactions on Systems and referenced in Journal of Information Technology & Software Engineering

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