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Robustness analysis of neutral BAMNN with time delays

机译:带时间延迟中性BAMN的鲁棒性分析

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This paper is studied with robustness of neutral BAMNN (Bidirectional Associative Memory neural networks) with time delays. We discuss that how much neutral term contraction coefficient and time delay are allowed to ensure the global exponential stable of neutral BAMNN with time delays. By using some transcendental equations, a criterion of global exponential stable is derived for neutral BAMNN with time delays. We proved in theory, if contraction coefficient of neutral terms and time delays are smaller than the results arrived, then the BAMNN also is globally exponentially stable. Finally, an example is provided to show the correctness of our analysis and the effectiveness of the theoretical results.
机译:本文采用了中性BAMNN(双向关联内存神经网络)的稳健性,随着时间的推迟。我们讨论了允许多少中性术语收缩系数和时间延迟,以确保具有时间延迟的中性BAMN的全球指数稳定。通过使用一些超越方程,导出全局指数稳定的标准对于具有时间延迟的中性Bamnn。我们证明了理论上,如果中性术语和时间延迟的累计系数小于结果到达,则Bamnn也是全球指数稳定的。最后,提供了一个例子以显示我们分析的正确性和理论结果的有效性。

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