A new stability criterion for bidirectional associative memory neural networks of neutral-type
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摘要
In the paper, the global asymptotic stability of equilibrium is considered for continuous bidirectional associative memory (BAM) neural networks of neutral type by using the Lyapunov method. A new stability criterion is derived in terms of linear matrix inequality (LMI) to ascertain the global asymptotic stability of the BAM. The LMI can be solved easily by various convex optimization algorithms. A numerical example is illustrated to verify our result.
论文关键词：Global stability,BAM neural network,Delay,Linear matrix inequality,Lyapunov method
论文评审过程：Available online 1 November 2007.
论文官网地址：https://doi.org/10.1016/j.amc.2007.10.032
