On periodic solutions of a two-neuron network system with sigmoidal activation functions

Cheng Hsiung Hsu, Suh Yuh Yang, Ting Hui Yang, Tzi Sheng Yang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper we study the existence, uniqueness and stability of periodic solutions for a two-neuron network system with or without external inputs. The system consists of two identical neurons, each possessing nonlinear feedback and connected to the other neuron via a nonlinear sigmoidal activation function. In the absence of external inputs but with appropriate conditions on the feedback and connection strengths, we prove the existence, uniqueness and stability of periodic solutions by using the Poincaré-Bendixson theorem together with Dulac's criterion. On the other hand, for the system with periodic external inputs, combining the techniques of the Liapunov function with the contraction mapping theorem, we propose some sufficient conditions for establishing the existence, uniqueness and exponential stability of the periodic solutions. Some numerical results are also provided to demonstrate the theoretical analysis.

Original languageEnglish
Pages (from-to)1405-1417
Number of pages13
JournalInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume16
Issue number5
DOIs
StatePublished - May 2006

Keywords

  • Contraction mapping theorem
  • Dulac's criterion
  • Liapunov functions
  • Neural networks
  • Periodic solutions
  • Poincaré-Bendixson theorem

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