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Existence and exponential stability of periodic solutions for a class of Cohen–Grossberg neural networks with bounded and unbounded delays

Authors
Journal
Nonlinear Analysis Real World Applications
1468-1218
Publisher
Elsevier
Publication Date
Volume
8
Issue
3
Identifiers
DOI: 10.1016/j.nonrwa.2006.03.005
Keywords
  • Cohen–Grossberg Neural Networks
  • Periodic Solution
  • Exponential Stability
  • Coincidence Degree Theory
  • Bounded And Unbounded Delays
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract In this paper, a class of Cohen–Grossberg neural networks with bounded and unbounded delays are considered. Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnections, sufficient conditions for the existence and exponential stability of the periodic solutions are established by using the coincidence degree theorem and differential inequality techniques. The results of this paper are new and they complement previously known results.

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