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Improved stability analysis of uncertain neutral type neural networks with leakage delays and impulsive effects

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  • Raja, R.
  • Zhu, Quanxin
  • Senthilraj, S.
  • Samidurai, R.

Abstract

This paper focuses on the stability analysis for neural networks of neutral type with leakage delays and impulsive effects. The discrete delays are assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By utilizing the Lyapunov functional method, Jensen’s integral inequality and introducing some free-weighting matrices, some new delay-derivative-dependent stability criteria are established for the neutral type neural network. The obtained stability criteria are stated in terms of linear matrix inequalities. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones.

Suggested Citation

  • Raja, R. & Zhu, Quanxin & Senthilraj, S. & Samidurai, R., 2015. "Improved stability analysis of uncertain neutral type neural networks with leakage delays and impulsive effects," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 1050-1069.
    • Handle: RePEc:eee:apmaco:v:266:y:2015:i:c:p:1050-1069
    DOI: 10.1016/j.amc.2015.06.030
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    References listed on IDEAS

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    1. Liu, Hailin & Chen, Guohua, 2007. "Delay-dependent stability for neural networks with time-varying delay," Chaos, Solitons & Fractals, Elsevier, vol. 33(1), pages 171-177.
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    3. Park, Ju H. & Kwon, O.M., 2009. "Global stability for neural networks of neutral-type with interval time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1174-1181.
    4. Cho, Hyun J. & Park, Ju H., 2007. "Novel delay-dependent robust stability criterion of delayed cellular neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 32(3), pages 1194-1200.
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    Cited by:

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    2. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    3. Zhang, Guodong & Zeng, Zhigang, 2018. "Exponential stability for a class of memristive neural networks with mixed time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 544-554.
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    5. Li, Hong-Li & Kao, Yonggui & Hu, Cheng & Jiang, Haijun & Jiang, Yao-Lin, 2021. "Robust exponential stability of fractional-order coupled quaternion-valued neural networks with parametric uncertainties and impulsive effects," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
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    8. Balasundaram, K. & Raja, R. & Pratap, A. & Chandrasekaran, S., 2019. "Impulsive effects on competitive neural networks with mixed delays: Existence and exponential stability analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 290-302.
    9. Cao, Jinde & Guerrini, Luca & Cheng, Zunshui, 2019. "Stability and Hopf bifurcation of controlled complex networks model with two delays," Applied Mathematics and Computation, Elsevier, vol. 343(C), pages 21-29.
    10. Ren, Yong & He, Qian & Gu, Yuanfang & Sakthivel, R., 2018. "Mean-square stability of delayed stochastic neural networks with impulsive effects driven by G-Brownian motion," Statistics & Probability Letters, Elsevier, vol. 143(C), pages 56-66.
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    12. Maharajan, C. & Raja, R. & Cao, Jinde & Rajchakit, G. & Alsaedi, Ahmed, 2018. "Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 268-282.

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