Mittag-Leffler stability analysis of fractional discrete-time neural networks via fixed point technique

Guo–Cheng Wu, Thabet Abdeljawad, Jinliang Liu, Dumitru Bǎleanu, Kai-Teng Wu

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Abstract

A class of semilinear fractional difference equations is introduced in this paper. The fixed point theorem is adopted to find stability conditions for fractional difference equations. The complete solution space is constructed and the contraction mapping is established by use of new equivalent sum equations in form of a discrete Mittag-Leffler function of two parameters. As one of the application, finite-time stability is discussed and compared. Attractivity of fractional difference equations is proved, and Mittag-Leffler stability conditions are provided. Finally, the stability results are applied to fractional discrete-time neural networks with and without delay, which show the fixed point technique’s efficiency and convenience.

Abstract of "Mittag-Leffler stability analysis of fractional discrete-time neural networks via fixed point technique" by Guo–Cheng Wu, Thabet Abdeljawad, Jinliang Liu et al., https://doi.org/10.15388/na.2019.6.5, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.

Record

Archive ID
doi:10.15388/na.2019.6.5
Published
Nov 7, 2019
Venue
Nonlinear Analysis Modelling and Control
DOI
10.15388/na.2019.6.5
Categories
Nonlinear Differential Equations Analysis
License
cc-by
Provenance
openalex

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