SICNNs with Li-Yorke chaotic outputs on a time scale

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Fen M. O., Fen F. T.

NEUROCOMPUTING, vol.237, pp.158-165, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 237
  • Publication Date: 2017
  • Doi Number: 10.1016/j.neucom.2016.09.073
  • Journal Name: NEUROCOMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.158-165
  • Keywords: Shunting inhibitory cellular neural networks, Time scales, Li-Yorke chaos, Proximality, Frequent separation, Chaos control, CELLULAR NEURAL-NETWORKS, ANTIPERIODIC SOLUTIONS, POSTSYNAPTIC CURRENTS, DELAYS, SYNCHRONIZATION, STABILITY, FEEDBACK
  • TED University Affiliated: Yes

Abstract

The existence of Li-Yorke chaos in the dynamics of shunting inhibitory cellular neural networks (SICNNs) on time scales is investigated. It is rigorously proved by taking advantage of external inputs that the outputs of SICNNs exhibit Li-Yorke chaos. The theoretical results are supported by simulations, and the controllability of chaos on the time scale is demonstrated by means of the Pyragas control technique. This is the first time in the literature that the existence as well as the control of chaos are provided for neural networks on time scales.