Multiperiodicity analysis and numerical simulation of discrete-time transiently chaotic non-autonomous neural networks with time-varying delays

✍ Scribed by Zhenkun Huang; Sannay Mohamod; Honghua Bin

• Publisher: Elsevier Science
• Year: 2010
• Tongue: English
• Weight: 951 KB
• Volume: 15
• Category: Article
• ISSN: 1007-5704
• DOI: 10.1016/j.cnsns.2009.05.060

✦ Synopsis

sequence solutions Exponential stability Time-varying delays a b s t r a c t

In this paper, we investigate multiperiodicity analysis of discrete-time transiently chaotic neural networks, i.e., the coexistence and exponential stability of multiple periodic sequence solutions. By using analytic property of activation functions and Schauder's fixed point theorem, we attain the coexistence of 2 N periodic sequence solutions. Meanwhile, some new and simple criteria are derived for the networks to converge exponentially toward 2 N periodic sequence solutions. Our results are new and complement existing ones in the literature. Finally, computer numerical simulations are performed to illustrate multiperiodicity of discrete-time transiently chaotic neural networks.