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International Conference on Neural Information Processing

ICONIP 2012: Neural Information Processing pp 460–466Cite as

Suppression of Functional System with Markovian Switching

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7664))

Abstract

In this paper, we will investigate a class of functional system whose coefficient satisfies the local Lipschitz condition and the one-sided polynomial growth condition under Markovian switching. We introduce two appropriate intensity Brownian noise to perturb the system so as to suppress its potential explosion.

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Author information

Authors and Affiliations

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

    Lizhu Feng, Yi Shen & Zhuguo Li

  2. School of Mathematics and Computer Science, Jianghan University, Wuhan, 430056, China

    Lizhu Feng

Authors
  1. Lizhu Feng
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  2. Yi Shen
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  3. Zhuguo Li
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Feng, L., Shen, Y., Li, Z. (2012). Suppression of Functional System with Markovian Switching. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_56

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  • DOI: https://doi.org/10.1007/978-3-642-34481-7_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34480-0

  • Online ISBN: 978-3-642-34481-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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