Stability and synchronization of a fractional BAM neural network system of high-order type

2020/09/29 by Sakina Othmani, Othmani, Sakina, Nasser‐eddine Tatar +1
Computer Science · Physics and Astronomy · #26A33 #92B20 #93D20 #Chaos control and synchronization #Dynamical Systems (math.DS) #FOS: Mathematics #G.0 #Neural Networks Stability and Synchronization #Neural Networks and Applications

paper · pdf · doi:10.48550/arxiv.2009.14300

openalex publication_date 2020/09/29 · openalex created_date 2020/10/08 · openalex updated_date 2026/07/28

Abstract

In this paper, stability and synchronization of a Caputo fractional BAM neural network system of high-order type and neutral delays are examined. A mixture of properties of fractional calculus, Laplace transform, and analytical techniques is used to derive Mittag-Leffler stability and synchronization for two classes of activation functions. A fractional version of Halanay inequality is utilized to deal with the fractional character of the system and some suitable evaluations and handling to cope with the higher order feature. Another feature is the treatment of unbounded activation functions. Explicit examples to validate the theoretical outcomes are shown at the end.

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