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Dynamic Systems with Time Delays: Stability and Control pp 155–176Cite as

Stability Analysis for Neural Networks with Time-Varying Delay

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Abstract

This chapter is devoted to the study of the stability of time-delay neural networks in both continuous and discrete contexts. Augmented Lyapunov–Krasovskii (L–K) functionals are deliberately constructed for both continuous and discrete cases, in which state and delay information of neural networks is fully taken into account. During the process of dealing with the time derivative (or the forward difference) of L–K functionals, the integral (or summation) inequalities are employed to estimate integral (or summation) terms. Consequently, more relaxed conditions are derived in the forms of linear matrix inequalities. Several numerical examples are presented to show the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Yeungnam University, Gyeongsan-si, Korea (Republic of)

    Ju H. Park

  2. Division of Electronic Engineering, Chonbuk National University, Jeonju, Korea (Republic of)

    Tae H. Lee

  3. Control and Computer Engineering, North China Electric Power University, Beijing, China

    Yajuan Liu

  4. School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China

    Jun Chen

Authors
  1. Ju H. Park
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  2. Tae H. Lee
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  3. Yajuan Liu
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  4. Jun Chen
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Corresponding author

Correspondence to Ju H. Park .

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Cite this chapter

Park, J., Lee, T.H., Liu, Y., Chen, J. (2019). Stability Analysis for Neural Networks with Time-Varying Delay. In: Dynamic Systems with Time Delays: Stability and Control. Springer, Singapore. https://doi.org/10.1007/978-981-13-9254-2_6

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