Journal of applied mathematics & informatics

한국전산응용수학회 (The Korean Society for Computational and Applied Mathematics)
권호 표지
DOI QR코드

DOI QR Code

LOCAL SYNCHRONIZATION OF MARKOVIAN NEURAL NETWORKS WITH NONLINEAR COUPLING

  • LI, CHUNJI (Department of Mathematics, Northeastern University) ;
  • REN, XIAOTONG (Department of Mathematics, Northeastern University)
  • 투고 : 2017.01.23
  • 심사 : 2017.04.10
  • 발행 : 2017.05.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In order to react the dynamic behavior of the system more actually, it is necessary to solve the first problem of synchronization for Markovian jump complex network system in practical engineering problem. In this paper, the problem of local stochastic synchronization for Markovian nonlinear coupled neural network system is investigated, including nonlinear coupling terms and mode-dependent delays, that is less restriction to other system. By designing the Lyapunov-Krasovskii functional and applying less conservative inequality, we get a new criterion to ensure local synchronization in mean square for Markovian nonlinear coupled neural network system. The criterion introduced some free matrix variables, which are less conservative. The simulation confirmed the validity of the conclusion.

키워드

참고문헌

  1. Q. Ma, S. Xu and Y. Zou, Stability and synchronization for Markovian jump neural net- works with partly unknown transition probabilities, Neurocomputing 74 (2011) 3404-3411. https://doi.org/10.1016/j.neucom.2011.05.018
  2. Y. Liu, Z. Wang, J. Liang and X. Liu, Synchronization of coupled neutral-type neural networks with jumping-mode-dependent discrete and unbounded distributed delays, IEEE Trans. Cybern. 43 (2013) 102-114. https://doi.org/10.1109/TSMCB.2012.2199751
  3. J. Wang, H. Zhang, Z. Wang and H. Liang, Local stochastic synchronization for Markovian neutral-type complex networks with partial information on transition probabilities, Neurocomputing 149(2015) 983-992. https://doi.org/10.1016/j.neucom.2014.07.035
  4. T.H. Lee, H.P. Ju, and S.M. Lee, Robust sampled-data control with random missing data scenario, International Journal of Control. 87 (2014) 1957-1969. https://doi.org/10.1080/00207179.2014.896476
  5. C.W. Wu and L.O. Chua, Synchronization in an array of linearly coupled dynamical systems, IEEE Trans. Circuits Syst. I: Fundam. Theory Appl. 42 (1995) 430-447. https://doi.org/10.1109/81.404047
  6. W. Yu, J. Cao, G. Chen, J. Lu, J. Han and W. Wei, Local synchronization of a complex network model, IEEE Trans. Syst. Man Cybern. B 39 (2009) 230-241. https://doi.org/10.1109/TSMCB.2008.2004964
  7. Q. Song, and Z. Zhao, Cluster, local and complete synchronization in coupled neural net- works with mixed delays and nonlinear coupling, Neural Comput. Appl. 24 (2014) 1101-1113. https://doi.org/10.1007/s00521-012-1296-4
  8. X. Liu and H. Xi, Synchronization of neutral complex dynamical networks with Markovian switching based on sampled-data controller, Neurocomputing 139 (2014) 163-179. https://doi.org/10.1016/j.neucom.2014.02.048
  9. Y. Liu, Z. Wang and X. Liu, Global exponential stability of generalized recurrent neural networks with discrete and distributed delays, Neural Networks 19 (2006) 667-675. https://doi.org/10.1016/j.neunet.2005.03.015
  10. H. Chang, Y. Fang and S. Lou, Stabilization of a class of continuous-time singular Markov jump systems, Control and Decision 27 (2012) 641-645.