Chaos, multiplicity, crisis, and synchronicity in higher order neural networks

We study a randomly diluted higher-order network of spinlike neurons that interact via Hebbian-type connections and derive and solve exact dynamical equations for a general block-sequential updating algorithm. The system has a variety of static and oscillatory solutions. The bifurcation parameters i...

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Main Authors:	Wang, Lipo., Ross, John.
Other Authors:	School of Electrical and Electronic Engineering
Format:	Article
Language:	English
Published:	2012
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/94715 http://hdl.handle.net/10220/8128
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-94715
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spelling	sg-ntu-dr.10356-947152020-03-07T14:02:35Z Chaos, multiplicity, crisis, and synchronicity in higher order neural networks Wang, Lipo. Ross, John. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering We study a randomly diluted higher-order network of spinlike neurons that interact via Hebbian-type connections and derive and solve exact dynamical equations for a general block-sequential updating algorithm. The system has a variety of static and oscillatory solutions. The bifurcation parameters in the present model include neuronal interaction coefficients, the synchronicity parameter, and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. Published version 2012-05-23T02:43:51Z 2019-12-06T19:00:58Z 2012-05-23T02:43:51Z 2019-12-06T19:00:58Z 1991 1991 Journal Article Wang, L., & Ross, J. (1991). Chaos, multiplicity, crisis, and synchronicity in higher order neural networks. Physical Review A, vol. 44(4), pp. R2259 - R2262. https://hdl.handle.net/10356/94715 http://hdl.handle.net/10220/8128 10.1103/PhysRevA.44.R2259 en Physical review A © 1991 The American Physical Society. This paper was published in Physical Review A and is made available as an electronic reprint (preprint) with permission of American Physical Society. The paper can be found at the following official URL: [http://dx.doi.org/10.1103/PhysRevA.44.R2259]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 4 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Wang, Lipo. Ross, John. Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
description	We study a randomly diluted higher-order network of spinlike neurons that interact via Hebbian-type connections and derive and solve exact dynamical equations for a general block-sequential updating algorithm. The system has a variety of static and oscillatory solutions. The bifurcation parameters in the present model include neuronal interaction coefficients, the synchronicity parameter, and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Wang, Lipo. Ross, John.
format	Article
author	Wang, Lipo. Ross, John.
author_sort	Wang, Lipo.
title	Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
title_short	Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
title_full	Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
title_fullStr	Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
title_full_unstemmed	Chaos, multiplicity, crisis, and synchronicity in higher order neural networks
title_sort	chaos, multiplicity, crisis, and synchronicity in higher order neural networks
publishDate	2012
url	https://hdl.handle.net/10356/94715 http://hdl.handle.net/10220/8128
_version_	1681049833654190080

Chaos, multiplicity, crisis, and synchronicity in higher order neural networks

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