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Existence and exponential stability of almost‐periodic solutions for neutral BAM neural networks with time‐varying delays in leakage terms on time scales
Author(s) -
Gao Jin,
Wang Qiru,
Lin Yuan
Publication year - 2016
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.3574
Subject(s) - uniqueness , bidirectional associative memory , exponential stability , mathematics , leakage (economics) , artificial neural network , exponential function , stability (learning theory) , exponential dichotomy , associative property , control theory (sociology) , content addressable memory , mathematical analysis , pure mathematics , computer science , differential equation , nonlinear system , artificial intelligence , physics , control (management) , quantum mechanics , machine learning , economics , macroeconomics
This paper is concerned with neutral bidirectional associative memory neural networks with time‐varying delays in leakage terms on time scales. Some sufficient conditions on the existence, uniqueness, and global exponential stability of almost‐periodic solutions are established. An example is presented to illustrate the feasibility and effectiveness of the obtained results. Copyright © 2015 John Wiley & Sons, Ltd.