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

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...

Full description

Bibliographic Details
Main Authors: Guo-Cheng Wu, Thabet Abdeljawad, Jinliang Liu, Dumitru Baleanu, Kai-Teng Wu
Format: Article
Language:English
Published: Vilnius University Press 2019-11-01
Series:Nonlinear Analysis
Subjects:
Online Access:http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/14844
Description
Summary: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.
ISSN:1392-5113
2335-8963