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Stability of Neural Networks with Both Impulses and Time-Varying Delays on Time Scale

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Advances in Neural Networks – ISNN 2011 (ISNN 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6675))

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Abstract

In this paper, the stability of neural networks with both impulses and time-varying delays on time scale is investigated, the existence of Delta derivative of time-varying delays is not assumed. By employing time scale calculous theory, free weighting matrix method and linear matrix inequality (LMI) technique, a delay-dependent sufficient condition is obtained to ensure the stability of equilibrium point for neural networks with both impulses and time-varying delays on time scale. An example with simulations is given to show the effectiveness of the theory.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Huzhou Teachers College, Huzhou, 313000, China

    Yupei Lv

  2. Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China

    Bo Zhou & Qiankun Song

Authors
  1. Yupei Lv
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  2. Bo Zhou
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  3. Qiankun Song
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Editor information

Editors and Affiliations

  1. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Derong Liu

  2. College of Information Science and Engineering, Shenyang, Northeastern University, 110004, Liaoing, China

    Huaguang Zhang

  3. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios Polycarpou

  4. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  5. Deptartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, RI 02881, Kingston, USA

    Haibo He

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© 2011 Springer-Verlag Berlin Heidelberg

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Lv, Y., Zhou, B., Song, Q. (2011). Stability of Neural Networks with Both Impulses and Time-Varying Delays on Time Scale. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21105-8_25

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  • DOI: https://doi.org/10.1007/978-3-642-21105-8_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21104-1

  • Online ISBN: 978-3-642-21105-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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