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International Symposium on Neural Networks

ISNN 2008: Advances in Neural Networks - ISNN 2008 pp 158–167Cite as

Delay-Dependent Global Asymptotic Stability in Neutral-Type Delayed Neural Networks with Reaction-Diffusion Terms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5263))

Abstract

In this paper, the global uniform asymptotic stability is studied for a class of delayed neutral-type neural networks with reaction-diffusion terms. By constructing appropriate Lyapunov-Krasovskii functional and using the linear matrix inequality (LMI) approach, several sufficient conditions are obtained for ensuring the system to be globally uniformly asymptotically stable. A numerical example is given in the end of this paper to demonstrate the effectiveness and applicability of the proposed criteria.

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Authors and Affiliations

  1. Department of Mathematics, Linyi Normal University, Linyi, 276005, China

    Jianlong Qiu, Yinlai Jin & Qingyu Zheng

Authors
  1. Jianlong Qiu
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  2. Yinlai Jin
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  3. Qingyu Zheng
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Qiu, J., Jin, Y., Zheng, Q. (2008). Delay-Dependent Global Asymptotic Stability in Neutral-Type Delayed Neural Networks with Reaction-Diffusion Terms. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87732-5_18

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  • DOI: https://doi.org/10.1007/978-3-540-87732-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87731-8

  • Online ISBN: 978-3-540-87732-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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