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Anti-periodic Solutions of Inertial Neural Networks with Time Delays

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Abstract

In this paper, the exponential stability of anti-periodic solutions for inertial neural networks with time delays is investigated. First, by properly chosen variable substitution the system is transformed to first order differential equation. Second, some sufficient conditions which can ensure the existence and exponential stability of anti-periodic solutions for the system are obtained by using Lyapunov method and uniformly converges. Finally, an example is given to illustrate the effectiveness of the results.

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Authors and Affiliations

  1. Department of Mathematics, Shaoxing University, Shaoxing, Zhejiang, China

    Yunquan Ke & Chunfang Miao

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  1. Yunquan Ke
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  2. Chunfang Miao
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Correspondence to Yunquan Ke.

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Ke, Y., Miao, C. Anti-periodic Solutions of Inertial Neural Networks with Time Delays. Neural Process Lett 45, 523–538 (2017). https://doi.org/10.1007/s11063-016-9540-z

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