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LMI based stability criterion for uncertain neutral-type neural networks with discrete and distributed delays

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper studies the problem of robust stability analysis for uncertain neutral-type neural networks with discrete and distributed delays. By constructing an appropriate Lyapunov- Krasovskii functional, new delay-dependent criteria are obtained. We utilized the free-weighting matrices approach and bounding lemmas to estimate the derivative of the Lyapunov-Krasovskii functional. The stability criterion are established in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to illustrate the effectiveness of the proposed method.
Rocznik
Strony
77--97
Opis fizyczny
Bibliogr. 36 poz.
Twórcy
autor
  • New Horizon College of Engineering, Marathhalli, Bangalore, 560103, India
  • RNS Institute of Technology, Channasandra, Bangalore, 560098, India
autor
  • Department of Mathematics, Thiruvalluvar University, Vellore - 632 115, Tamilnadu, India
Bibliografia
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  • Balasubramaniam, P., Nagamani G. and Rakkiyappan, R. (2010) Global passivity analysis of interval neural networks with discrete and distributed delays of neutral type. Neural Processing Letters 32 (2), 109–130.
  • Chen, J. Sun, J., Liu, G. and Rees, D. (2010) New delay-dependent stability criteria for neural networks with time-varying interval delay. Phys. Lett. A, 374, 4397-4405.
  • Duan, W., Du, B., You, J. and Zou, Y.(2013) Synchronization criteria for neutral complex dynamic networks with interal time-varying coupling delays. Asian J. Cont. 15, 1385–1396.
  • Feng, J., Xu, S.Y. and Zou, Y. (2009) Delay-dependent stability of neutral type neural networks with distributed delays. Neurocomputing 72, 2576-2580.
  • Ge, C., Hu, C. and Guan, X. (2014) New delay-dependent stability criteria for neural networks with time-varying delay using delay-decomposition approach. IEEE Trans. Neural Netw. 25, 1378–1383.
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  • Gu, K., Kharitonov, V. L. and Chen, J. (2003) Stability of time delay systems. Birkhäuser, Boston.
  • Guo, W., Austin, F. and Chen, S. (2010) Global synchronization of nonlinearly coupled complex networks with non-delayed coupling. Commun. Nonlinear Sci. Numer. Simul., 15, 1631–1639.
  • He, Y., Liu, G., Rees, D. and Wu, M. (2007) Stability analysis for neural networks with time-varying interval delay. IEEE Trans. Neural Netw., 18, 1850-1854.
  • Kwon, O.M., Lee, S.M., Park, J.H. and Cha, E.J. (2012) New approaches on stability criteria for neural networks with interval time-varying delays. Appl. Math. Comput. 213, 9953-9964.
  • Lee, S.M., Kwon, O.M. and Park, Ju H. (2010) A novel delay-dependent criterion for delayed neural networks of neutral type. Phys. Lett. A 374, 1843-1848.
  • Li, Y., Zhong, S., Cheng, J., Shi, K. and Ren, J. (2016) New passivity criteria for uncertain neural networks with time-varying delay. Neurocomputing 171, 1003–1012.
  • Liu, D. (1997) Cloning template design of cellular neural networks for associative memories. IEEE Trans. Circuit. Syst. 44, 646-650.
  • Liu, P. (2009) Robust exponential stability for uncertain time-varying delay systems with delay dependence. J. Franklin Inst. 346, 958–968.
  • Nagamani, G. and Balasubramaniam, P. (2012) Delay-dependent passivity criteria for uncertain switched neural networks of neutral type with interval time-varying delay. Physica Scripta 85 (4), 045010.
  • Park, P., Ko, J. W. and Jeong, C. (2011) Reciprocally convex approach to stability of systems with time-varying delays. Automatica 47, 235-238.
  • Petersen, I.R. (1987) A stabilization algorithm for a class of uncertain linear systems. Systems and Control Letters 8, 351-357.
  • Ren, Y., Feng, Z. and Sun, G. (2016) Improved stability conditions for uncertain neutral-type systems with time-varying delays. Int. J. Syst. Sci. 47, 1982-1993.
  • Saravanakumar, R., Syed Ali, M., Cao, J. and Huang, H. (2016) H1 state estimation of generalised neural networks with interval time-varying delays. International Journal of Systems Science 47 (16), 3888–3899.
  • Shi, K., Zhu, H., Zhong, S., Zeng, Y. and Zhang, Y. (2015) New stability analysis for neutral type neural networks with discrete and distributed delays using a multiple integral approach. J. Franklin Inst. 352, 155-176.
  • Song, Q. K. (2008) Exponential stability of recurrent neural networks with both time-varying delays and general activation functions via LMI approach. Neurocomputing, 71, 2823-2830.
  • Sun, J., Liu, G.P., Chen, J. and Rees, D. (2009) Improved stability criteria for neural networks with time-varying delay. Phys. Lett. A, 373, 342-348.
  • Syed Ali, M. (2011 ) Global asymptotic stability of stochastic fuzzy recurrent neural networks with mixed time-varying delays. Chin Phys B 20 (8), 080201.
  • Syed Ali, M. (2014) Stability analysis ofMarkovian jumping stochastic Cohen–Grossberg neural networks with discrete and distributed time varying delays. Chinese Physics B 23 (6), 060702.
  • Syed Ali, M., Saravanakumar, R. and Zhu, Q. (2015) Less conservative delay-dependent control of uncertain neural networks with discrete interval and distributed time-varying delays. Neurocomputing 66, 84–95.
  • Syed Ali, M., Arik, S. and Saravanakmuar, R. (2015) Delay-dependent stability criteria of uncertain Markovian jump neural networks with discrete interval and distributed time-varying delays. Neurocomputing 158, 167–173.
  • Syed Ali, M. and Saravanan, S. (2016) Robust finite-time H1 control for a class of uncertain switched neural networks of neutral-type with distributed time varying delays. Neurocomputing, 177, 454-468.
  • Syed Ali, M., Saravanakumar, R., Ahn, C. K. and Karimi, H. R. (2017) Stochastic H1 filtering for neural networks with leakage delay and mixed time-varying delays. Information Sciences 388, 118–134.
  • Syed Ali, M., Gunasekaran, N., Ahn, C.K. and Shi, P. (2018) Sampleddata stabilization for fuzzy genetic regulatory networks with leakage delays. IEEE/ACM Transactions on computational biology and bioinformatics, 15, 271-285.
  • Tian, J. and Zhong, S.M. (2011) Improved delay-dependent stability criterion for neural networks with time-varying delay. Appl. Math. Comput. 217, 10278-10288.
  • Tian, J. K., Xiong, W. J. and Xu, F. (2014) Improved delay-partitioning method to stability analysis for neural networks with discrete and distributed time-varying delays. Appl. Math. Comput. 233, 152–164.
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-03b47ab3-27d0-4200-908f-fffa74062363
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