Title: Spatial complexity in multi-layer cellular neural networks
Authors: Ban, Jung-Chao
Chang, Chih-Hung
Lin, Song-Sun
Lin, Yin-Heng
應用數學系
Department of Applied Mathematics
Keywords: Cellular neural networks;Sofic shift;Spatial entropy;Dynamical zeta function
Issue Date: 15-Jan-2009
Abstract: 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.
URI: http://dx.doi.org/10.1016/j.jde.2008.05.004
http://hdl.handle.net/11536/7741
ISSN: 0022-0396
DOI: 10.1016/j.jde.2008.05.004
Journal: JOURNAL OF DIFFERENTIAL EQUATIONS
Volume: 246
Issue: 2
Begin Page: 552
End Page: 580
Appears in Collections:Articles


Files in This Item:

  1. 000261714900005.pdf