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Global Stability of Complex-Valued Neural Networks with Time-Delays and Impulsive Effects

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10636))

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Abstract

The global exponential stability problem for a class of complex-valued recurrent neural networks with both asynchronous time-varying delays and impulse is concerned in this paper. By using Schur complement and Lyapunov functional, some new sufficient criteria to ascertain globally exponential stability of the equilibrium point are obtained in terms of linear matrix inequality. An example is given to illustrate the effectiveness of the results.

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References

  1. Liu, X., Chen, T.: Global exponential stability for complex-valued recurrent neural networks with asynchronous time delays. IEEE Trans. Neural Netw. Learn. Syst. 27(3), 593–606 (2016)

    Article  MathSciNet  Google Scholar 

  2. Lu, W., Chen, T.: New conditions on global stability of cohen-grossberg neural networks. Neural Comput. 15, 1173 (1989)

    Article  MATH  Google Scholar 

  3. Bohner, M., Rao, V.S.: Global stability of complex-valued neural networks on time scales. Differ. Equ. Dyn. Syst. 19, 3–11 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  4. Sree, H., Murthy, G.: Global dynamics of a class of complex-valued neural networks. Int. J. Neural Syst. 18, 165–171 (2008)

    Article  Google Scholar 

  5. Jankowski, S., Lozowski, A., Zurada, J.: Complex-valued multistate nueral associative memory. IEEE Trans. Neural Netw. Learn. Syst. 7(6), 1491–1496 (1996)

    Article  Google Scholar 

  6. Lee, D.: Relexation of stability condition of the complex-valued neural networks. IEEE Trans. Neural Netw. Learn. Syst. 12(5), 1260–1262 (2001)

    Article  Google Scholar 

  7. Song, Q., Cao, J.: Stability analysis of Cohen-Grossberg neural network with both time-varying and continuously distributed delays. J. Comput. Appl. Math. 197(1), 188–203 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  8. Fang, T., Sun, J.: Stability of complex-valued recurrent neural networks with time-delays. IEEE Trans. Neural Netw. Learn. Syst. 25(9), 1709–1713 (2014)

    Article  Google Scholar 

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Acknowledgments

This work was supported by the Excellent Doctor Innovation Program of Xinjiang University (Grant No. XJUBSCX-2015006), the Excellent Doctor Innovation Program of Xinjiang Uyghur Autonomous Region (Grant No. XJGRI2016001), the National Natural Science Foundation of People’s Republic of China (Grant No. 61164004).

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Authors and Affiliations

  1. College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, China

    Dongwen Zhang, Haijun Jiang, Cheng Hu, Zhiyong Yu & Da Huang

Authors
  1. Dongwen Zhang
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  2. Haijun Jiang
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  3. Cheng Hu
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  4. Zhiyong Yu
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  5. Da Huang
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Corresponding author

Correspondence to Haijun Jiang .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Zhang, D., Jiang, H., Hu, C., Yu, Z., Huang, D. (2017). Global Stability of Complex-Valued Neural Networks with Time-Delays and Impulsive Effects. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10636. Springer, Cham. https://doi.org/10.1007/978-3-319-70090-8_84

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  • DOI: https://doi.org/10.1007/978-3-319-70090-8_84

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70089-2

  • Online ISBN: 978-3-319-70090-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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