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Global asymptotic stability conditions of delayed neural networks

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Abstract

Utilizing the Liapunov functional method and combining the inequality of matrices technique to analyze the existence of a unique equilibrium point and the global asymptotic stability for delayed cellular neural networks (DCNNs), a new sufficient criterion ensuring the global stability of DCNNs is obtained. Our criteria provide some parameters to appropriately compensate for the tradeoff between the matrix definite condition on feedback matrix and delayed feedback matrix. The criteria can easily be used to design and verify globally stable networks. Furthermore, the condition presented here is independent of the dalay parameter and is less restrictive than that given in the references.

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Authors and Affiliations

  1. Department of Electronic Engineering, Fudan University, 200433, Shanghai, P. R. China

    Zhou Dong-ming Associate Professor, Doctor & Zhang Li-ming Professor

  2. Department of Applied Mathematics, Southeast University, 210096, Nanjing, P. R. China

    Cao Jin-de

  3. Department of Electronic Engineering, Yunnan University, 650091, Kunming, P. R. China

    Zhou Dong-ming Associate Professor, Doctor

Authors
  1. Zhou Dong-ming Associate Professor, Doctor
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  2. Cao Jin-de
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  3. Zhang Li-ming Professor
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Corresponding authors

Correspondence to Zhou Dong-ming Associate Professor, Doctor or Zhang Li-ming Professor.

Additional information

Communicated by LIU Zeng-rong

Project supported by the National Natural Science Foundation of China (No. 60171036)

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Dong-ming, Z., Jin-de, C. & Li-ming, Z. Global asymptotic stability conditions of delayed neural networks. Appl Math Mech 26, 372–380 (2005). https://doi.org/10.1007/BF02440088

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  • DOI: https://doi.org/10.1007/BF02440088

Key words

Chinese Library Classification

2000 Mathematics Subject Classification

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