Global exponential synchronization of delayed BAM neural networks with reaction-diffusion terms and the Neumann boundary conditions

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作者
WeiYuan Zhang
JunMin Li
机构
[1] Xidian University,School of Science
[2] Xianyang Normal University,Institute of Maths and Applied Mathematics
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neural networks; reaction-diffusion; delays; global exponential synchronization; Lyapunov functional;
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摘要
In this article, a delay-differential equation modeling a bidirectional associative memory (BAM) neural networks (NNs) with reaction-diffusion terms is investigated. A feedback control law is derived to achieve the state global exponential synchronization of two identical BAM NNs with reaction-diffusion terms by constructing a suitable Lyapunov functional, using the drive-response approach and some inequality technique. A novel global exponential synchronization criterion is given in terms of inequalities, which can be checked easily. A numerical example is provided to demonstrate the effectiveness of the proposed results.
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