基于记忆电阻的混合延迟递归神经网络的耗散结果

2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP) Pub Date : 2015-11-01 DOI:10.1109/ICICIP.2015.7388205

Kai Zhong, Song Zhu, Qiqi Yang

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引用次数: 3

摘要

本文通过构造适当的李雅普诺夫泛函和运用一些解析技术，分析了一类具有离散和分布延迟的混合延迟的基于忆阻器的递归神经网络。得到了关于寻址神经网络耗散率的两个新的充分性准则。最后，通过数值算例对理论结果进行了验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Dissipativity results for memristor-based recurrent neural networks with mixed delays

This paper analyzes a class of memristor-based recurrent neural networks with mixed delays involving both discrete and distributed delays by constructing appropriate Lyapunov functionals and using some analytic techniques. Two new adequacy criteria concerning the dissipativity of the addressed neural networks are obtained. Finally, a numerical example is discussed in detail to substantiate our theoretical results.

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2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)

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