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时变时滞双向联想记忆神经网络的鲁棒稳定性 被引量：3

Robust stability of bi-directional associate memory neural networks with time varying delays
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摘要 通过构造适当的Lyapunov泛函分析了一类时变时滞双向联想记忆神经网络的平衡点稳定性问题。不要求激励函数的单调性和可微性,得到了保证时变时滞双向联想记忆神经网络的平衡点全局鲁棒渐近稳定的两个新判据。所得到的结果能够表示成线性矩阵不等式形式,进而易于用内点算法等方法来验证。通过仿真例子与其他文献中的一些结果进行比较,表明了本文所得结果的有效性。 Based on the construction of Lyapunov function, global stability problems were studied for bi-directional associate memory neural networks with time varying delays. Without monotonicity and differentiation assumptions on activation function, two sufficient conditions were derived for the global robust stability of equilibrium point. The obtained results possess a linear matrix inequality structure and can be efficiently solved by using interior-point algorithms. Comparison between our results and the previous ones through a numerical example was conducted, which implies the effectiveness of the proposed results.
作者 王占山 关焕新 张化光
机构地区 东北大学信息科学与工程学院
出处 《吉林大学学报（工学版）》 EI CAS CSCD 北大核心 2007年第6期1397-1401,共5页 Journal of Jilin University:Engineering and Technology Edition
基金 国家自然科学基金资助项目(60534010 60572070 60521003) 教育部长江学者计划及创新团队资助项目(IRT0421)
关键词 自动控制技术 双向联想记忆神经网络 时变时滞 鲁棒稳定 线性矩阵不等式 automatic control technology bi-directional associative memory （BAM） neural networks time varying delays robust stability linear matrix inequality （LMI）
分类号 TP183 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献13

  • 1王占山,张化光.多时变时滞神经网络的全局指数稳定[J].吉林大学学报（工学版）,2005,35(6):621-625. 被引量：5
  • 2Zhang H G, Wang Z S, Liu D R. Exponential stability analysis of neural networks with multiple time delays [J], Lecture Notes in Computer Science, 2005(3496) : 142-148.
  • 3Arik S. Global asymptotic stability analysis of bi-directional associative memory neural networks with time delays[J]. IEEE Transactions on Neural Networks, 2005, 16(3): 580-586.
  • 4Arik S, Tavsanoglu V. Global asymptotic stability analysis of bi-directional associative memory neural networks with constant time delays[J]. Neurocomputing, 2005, 68(1): 161-176.
  • 5Liao X F, Yu J B, Chen G R. Novel stability criteria for bi-directional associative memory neural networks with time delays[J]. International Journal of Circuits Theory and Applications, 2002, 30 (3): 519-546.
  • 6Zhang J Y, Yang Y R. Global stability analysis of bidirectional associative memory neural networks with time delay[J]. International Journal of Circuit Theory and Applications, 2001, 29(1): 185-196.
  • 7Zhao H Y. Exponential stability and periodic oscillatory of bi-directional associative memory neural network involving delays[J]. Neurocomputing, 2006, 69(3) : 424-448.
  • 8Liao X F, Yu J B. Qualitative analysis of bi-directional associative memory with time delay[J]. International Journal of Circuits Theory and Applications, 1998, 26(2): 219-229.
  • 9Cao J D. Global asymptotic stability of delayed bi-directional associative memory networks[J]. Applied Mathematics and Computations, 2003, 142 (2): 333-339.
  • 10张化光 季策 王占山.递归人工神经网络的定性分析和综合[M].北京:科学出版社,2004.170-218.

二级参考文献13

  • 1ZHANG H, WANG Z, LIU D. Exponential Stability Analysis of Neural Networks with Multiple Time Delays[J]. Lecture Notes in Computer Science, 2005,3519:142 - i48.
  • 2CHEN A, CAO J, HUANG L. Global Robust Stability of Interval Cellular Neural Networks with Time Varying Delays [ J ]. Chaos, Solitons and Fraetals, 2005,23(3) : 787 - 799.
  • 3ZHANG J, JINX. Global Stability Analysis in Delayed Hopfield Neural Network Models[ J]. Neural Networks,2000,13(7) : 745 -753.
  • 4JOY M P. On the Global Convergence of a Class of Functional Differential Equation with Applications in Neural Network Theory [ J ]. Journal of Mathematical Analysis and Applications, 1999,232( 1 ) : 61 -81.
  • 5张化光 季策 王占山.递归人工神经网络的定性分析和综合[M].北京:科学出版社,2004.170-218.
  • 6LIAO X, CHEN G, SANCHEZ E N. LMI-based Approach for Asymptotic Stability Analysis of Delayed Neural Networks [ J ]. IEEE Trans on Circuits and Systems-I, 2002, 49(7):1033- 1039.
  • 7LIAO X, WONG K- W, WU Z, CHEN G. Novel Robust Stability Criteria for Interval Delayed Hopfield Neural Networks[J]. IEEE Trans on Circuits and Systems -I, 2001,48(11) : 1355 - 1358.
  • 8LU W, RONG L, CHEN T. Global Convergence of Delayed Neural Network Systems [ J ]. International Journal of Neural Systems, 2003,13(3) : 193 -204.
  • 9ZHANG Q, WEI X, XU J. Global Exponential Stability of Hopfield Neural Networks with Continuously Distributed Delays[J]. Physics Letters A, 2003(315) : 431 -436.
  • 10CAO J, WANG J. Global Asymptotic Stability of a General Class of Recurrent Neural Networks with Timevarying Delays [ J ]. IEEE Trans on Circuits and Systems-I. 2003. 50 ( 1 ) : 34 - 44.

共引文献10

同被引文献33

引证文献3

二级引证文献11

吉林大学学报（工学版）
2007年 第6期

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