Unpredictable oscillations of SICNNs with delay

Fen M. O., Fen F. T.

NEUROCOMPUTING, vol.464, pp.119-129, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 464
  • Publication Date: 2021
  • Doi Number: 10.1016/j.neucom.2021.08.093
  • Journal Name: NEUROCOMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, zbMATH
  • Page Numbers: pp.119-129
  • Keywords: Unpredictable oscillation, Shunting inhibitory cellular neural networks, Rectangular input currents, Exponential stability, Unidirectional coupling, Delayed feedback control, CELLULAR NEURAL-NETWORKS, GENERALIZED SYNCHRONIZATION, PATTERN-RECOGNITION, EXPONENTIAL CONVERGENCE, ANTIPERIODIC SOLUTIONS, PERIODIC-SOLUTION, CHAOS, STABILITY
  • TED University Affiliated: Yes

Abstract

We rigorously prove that unpredictable oscillations take place in the dynamics of shunting inhibitory cellular neural networks (SICNNs) with delay when rectangular input currents generated by an unpredictable sequence are utilized. The existence, uniqueness, and exponential stability of such oscillations are discussed. The contraction mapping principle is applied to achieve the theoretical results. Numerical simulations supporting the presence of unpredictable oscillations are provided, and the transfer of unpredictable behavior between SICNNs under unidirectional coupling is demonstrated. It is also shown by means of the delayed feedback control method that the obtained unpredictable behavior is controllable. Moreover, an application to secure communication is discussed. (C) 2021 Elsevier B.V. All rights reserved.