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Discrete Fractional‐Order BAM Neural Networks with Leakage Delay: Existence and Stability Results
Author(s) -
Alzabut Jehad,
Tyagi Swati,
Abbas Syed
Publication year - 2020
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1918
Subject(s) - uniqueness , bidirectional associative memory , fractional calculus , mathematics , artificial neural network , stability (learning theory) , fixed point theorem , control theory (sociology) , associative property , leakage (economics) , fixed point , computer science , content addressable memory , pure mathematics , mathematical analysis , control (management) , artificial intelligence , economics , macroeconomics , machine learning
In this paper, a discrete model of fractional‐order bidirectional associative memory (BAM) neural networks with leakage delay is considered. Sufficient conditions are established for the existence, uniqueness and uniform stability of nontrivial solutions of the addressed model. Our approach is based on the implementation of the newly defined discrete fractional calculus, mathematical inequalities and fixed point theorems. We provide an example that supports the application of the theoretical results.