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Periodic Solutions for High-Order Cohen-Grossberg-Type BAM Neural Networks with Time-Delays

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Advances in Neural Networks – ISNN 2011 (ISNN 2011)

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Abstract

In this paper, the existence and exponential stability is studied of periodic solutions for a class of high-order Cohen-Grossberg-type BAM neural networks with time-delays. By differential mean value theorem, integral mean value theorem and poincar\(\acute{e}\) mapping, several sufficient conditions guaranteeing the existence, uniqueness and exponential stability of periodic solutions for high-order Cohen-Grossberg-type BAM neural networks with time-delays are given. An illustrative examples are also given in the end to show the effectiveness of our results.

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Authors and Affiliations

  1. Department of Mathematics, Shaoxing University, Shaoxing, 312000, P.R. China

    Yunquan Ke & Chunfang Miao

Authors
  1. Yunquan Ke
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  2. Chunfang Miao
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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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Ke, Y., Miao, C. (2011). Periodic Solutions for High-Order Cohen-Grossberg-Type BAM Neural Networks with Time-Delays. 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_44

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  • DOI: https://doi.org/10.1007/978-3-642-21105-8_44

  • 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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