Spatial complexity in multi-layer cellular neural networks
2008; Elsevier BV; Volume: 246; Issue: 2 Linguagem: Inglês
10.1016/j.jde.2008.05.004
ISSN1090-2732
AutoresJUNG-CHAO BAN, Chih‐Hung Chang, Song-Sun Lin, Yin-Heng Lin,
Tópico(s)Nonlinear Dynamics and Pattern Formation
ResumoThis 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.
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