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Boundedness and Stability for Discrete-Time Delayed Neural Network with Complex-Valued Linear Threshold Neurons

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  • Chengjun Duan
  • Qiankun Song

Abstract

The discrete-time delayed neural network with complex-valued linear threshold neurons is considered. By constructing appropriate Lyapunov-Krasovskii functionals and employing linear matrix inequality technique and analysis method, several new delay-dependent criteria for checking the boundedness and global exponential stability are established. Illustrated examples are also given to show the effectiveness and less conservatism of the proposed criteria.

Suggested Citation

  • Chengjun Duan & Qiankun Song, 2010. "Boundedness and Stability for Discrete-Time Delayed Neural Network with Complex-Valued Linear Threshold Neurons," Discrete Dynamics in Nature and Society, Hindawi, vol. 2010, pages 1-19, August.
    • Handle: RePEc:hin:jnddns:368379
    DOI: 10.1155/2010/368379
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    Cited by:

    1. Hao, Zhang & Xing-yuan, Wang & Peng-fei, Yan & Yu-jie, Sun, 2020. "Combination synchronization and stability analysis of time-varying complex-valued neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).

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