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Global Asymptotic Stability of Periodic Solutions for Neutral-Type Delayed BAM Neural Networks by Combining an Abstract Theorem of k-Set Contractive Operator with LMI Method

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Abstract

The paper considers the existence and global asymptotic stability of periodic solutions for a class of neutral-type BAM neural networks with time delays. By combining an abstract theorem of k-set contractive operator with LMI method as well as inequality techniques, a sufficient condition to guarantee the existence of periodic solutions for the above neutral-type BAM neural networks with time delays is established. Then by combining LMI method with inequality techniques, a sufficient condition of the global asymptotic stability of periodic solutions for the above neutral-type BAM neural networks is obtained. Our method and results on periodic solutions for the above neural networks are new and complementary to the existing papers.

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Authors and Affiliations

  1. College of Mathematics and Econometrics, Hunan University, Changsha, 410082, China

    Zhengqiu Zhang & Feng Lin

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  1. Zhengqiu Zhang
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  2. Feng Lin
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Correspondence to Zhengqiu Zhang or Feng Lin.

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Project supported by the Innovation Platform Open Fund in Hunan Province Colleges and Universities of China (No. 201485).

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Zhang, Z., Lin, F. Global Asymptotic Stability of Periodic Solutions for Neutral-Type Delayed BAM Neural Networks by Combining an Abstract Theorem of k-Set Contractive Operator with LMI Method. Neural Process Lett 50, 1571–1588 (2019). https://doi.org/10.1007/s11063-018-9941-2

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