Spatial complexity in multi-layer cellular neural networks

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题名:	Spatial complexity in multi-layer cellular neural networks
作者:	Ban,JC;Chang,CH;Lin,SS;Lin,YH
贡献者:	數學研究所
关键词:	COUPLED NONLINEAR OSCILLATORS;PATTERNS GENERATION;LATTICE MODELS;DISCRETE;PROPAGATION;SYSTEMS;CHAINS;CHAOS
日期:	2009
上传时间:	2010-06-29 19:38:56 (UTC+8)
出版者:	中央大學
摘要:	This study investigates the complexity of the global set of output patterns for one-dimensional multi-layer cellular neural networks with input. Applying labeling to the output space produces a sofic shift space. Two invariants, namely spatial entropy and dynamical zeta function, can be exactly computed by studying the induced sofic shift space. This study gives sofic shift a realization through a realistic model. Furthermore, a new phenomenon, the broken of symmetry of entropy, is discovered in multi-layer cellular neural networks with input. (C) 2008 Elsevier Inc. All rights reserved.
關聯:	JOURNAL OF DIFFERENTIAL EQUATIONS
显示于类别:	[數學研究所] 期刊論文

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