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Existence and exponential stability of almost periodic solutions for neutral‐type BAM neural networks with distributed leakage delays
Author(s) -
Xu Changjin,
Li Peiluan,
Pang Yicheng
Publication year - 2017
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.4132
Subject(s) - exponential stability , mathematics , complement (music) , exponential dichotomy , artificial neural network , leakage (economics) , exponential function , contraction principle , differential equation , control theory (sociology) , mathematical analysis , nonlinear system , computer science , fixed point theorem , physics , artificial intelligence , biochemistry , chemistry , macroeconomics , control (management) , quantum mechanics , complementation , economics , gene , phenotype
This paper is concerned with a class of neutral‐type BAM neural networks with distributed leakage delays. By applying the exponential dichotomy of linear differential equations, Lyapunov functional method and contraction mapping principle, we establish some sufficient conditions which ensure the existence and exponential stability of almost periodic solutions for such BAM neural networks. An example is given to illustrate the effectiveness of the theoretical findings. The results obtained in this article are completely new and complement the previously known studies. Copyright © 2016 John Wiley & Sons, Ltd.