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LMI-Based Lagrange Stability of CGNNs with General Activation Functions and Mixed Delays

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7331))

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Abstract

This paper deals with the problem on Lagrange stability of Cohen-Grossberg neural networks (CGNNs) with both mixed time delays and general activation functions. By virtue of Lyapunov functional and Halanay delay differential inequality, several criteria in linear matrix inequality form for Lagrange stability of CGNNs are obtained. Meanwhile, the limitation on the activation functions being bounded, monotonous and differentiable is released and detailed estimation of the globally exponentially attractive sets are also given out. Finally, concluding remark is given.

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Author information

Authors and Affiliations

  1. Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China

    Xiaohong Wang & Huan Qi

Authors
  1. Xiaohong Wang
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  2. Huan Qi
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, X., Qi, H. (2012). LMI-Based Lagrange Stability of CGNNs with General Activation Functions and Mixed Delays. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_52

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  • DOI: https://doi.org/10.1007/978-3-642-30976-2_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30975-5

  • Online ISBN: 978-3-642-30976-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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