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Dynamics in fractional-order neural networks

Authors
Journal
Neurocomputing
0925-2312
Publisher
Elsevier
Identifiers
DOI: 10.1016/j.neucom.2014.03.047
Keywords
  • Neural Networks
  • Fractional Order
  • Uniform Stability
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract This paper investigates a general class of neural networks with a fractional-order derivative. By using the contraction mapping principle, Krasnoselskii fixed point theorem and the inequality technique, some new sufficient conditions are established to ensure the existence and uniqueness of the nontrivial solution. Moreover, uniform stability of the fractional-order neural networks is proposed in fixed time-intervals. Finally, some examples are given to illustrate the effectiveness of theoretical results.

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