• Title/Summary/Keyword: global exponential stability

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GLOBAL EXPONENTIAL STABILITY OF ALMOST PERIODIC SOLUTIONS OF HIGH-ORDER HOPFIELD NEURAL NETWORKS WITH DISTRIBUTED DELAYS OF NEUTRAL TYPE

  • Zhao, Lili;Li, Yongkun
    • Journal of applied mathematics & informatics
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    • v.31 no.3_4
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    • pp.577-594
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    • 2013
  • In this paper, we study the global stability and the existence of almost periodic solution of high-order Hopfield neural networks with distributed delays of neutral type. Some sufficient conditions are obtained for the existence, uniqueness and global exponential stability of almost periodic solution by employing fixed point theorem and differential inequality techniques. An example is given to show the effectiveness of the proposed method and results.

EXISTENCE AND GLOBAL EXPONENTIAL STABILITY OF A PERIODIC SOLUTION TO DISCRETE-TIME COHEN-GROSSBERG BAM NEURAL NETWORKS WITH DELAYS

  • Zhang, Zhengqiu;Wang, Liping
    • Journal of the Korean Mathematical Society
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    • v.48 no.4
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    • pp.727-747
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    • 2011
  • By employing coincidence degree theory and using Halanay-type inequality technique, a sufficient condition is given to guarantee the existence and global exponential stability of periodic solutions for the two-dimensional discrete-time Cohen-Grossberg BAM neural networks. Compared with the results in existing papers, in our result on the existence of periodic solution, the boundedness conditions on the activation are replaced with global Lipschitz conditions. In our result on the existence and global exponential stability of periodic solution, the assumptions in existing papers that the value of activation functions at zero is zero are removed.

EXISTENCE AND EXPONENTIAL STABILITY OF ALMOST PERIODIC SOLUTIONS FOR CELLULAR NEURAL NETWORKS WITHOUT GLOBAL LIPSCHITZ CONDITIONS

  • Liu, Bingwan
    • Journal of the Korean Mathematical Society
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    • v.44 no.4
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    • pp.873-887
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    • 2007
  • In this paper cellular neutral networks with time-varying delays and continuously distributed delays are considered. Without assuming the global Lipschitz conditions of activation functions, some sufficient conditions for the existence and exponential stability of the almost periodic solutions are established by using the fixed point theorem and differential inequality techniques. The results of this paper are new and complement previously known results.

GLOBAL EXPONENTIAL STABILITY OF BAM FUZZY CELLULAR NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND IMPULSES

  • Li, Kelin;Zhang, Liping
    • Journal of applied mathematics & informatics
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    • v.29 no.1_2
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    • pp.211-225
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    • 2011
  • In this paper, a class of bi-directional associative memory (BAM) fuzzy cellular neural networks with distributed delays and impulses is formulated and investigated. By employing an integro-differential inequality with impulsive initial conditions and the topological degree theory, some sufficient conditions ensuring the existence and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on the delay kernel functions and system parameters. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

EXPONENTIAL STABILITY OF A CLASS OF NONLINEAR DIFFERENCE EQUATIONS IN BANACH SPACES

  • Nguyen, Sinh Bay;Le, Van Hien;Hieu, Trinh
    • Communications of the Korean Mathematical Society
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    • v.32 no.4
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    • pp.851-864
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    • 2017
  • The problems of global and local exponential stability analysis of a class of nonlinear non-autonomous difference equations in Banach spaces are studied in this paper. By a novel comparison technique, new explicit exponential stability conditions are derived. Numerical examples are given to illustrate the effectiveness of the obtained results.

STABILITY OF IMPULSIVE CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS

  • Zhang, Lijuan;Yu, Lixin
    • Journal of applied mathematics & informatics
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    • v.29 no.5_6
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    • pp.1327-1335
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    • 2011
  • This paper demonstrates that there is a unique exponentially stable equilibrium state of a class of impulsive cellular neural network with delays. The analysis exploits M-matrix theory and generalized comparison principle to derive some easily verifiable sufficient conditions for the global exponential stability of the equilibrium state. The results extend and improve earlier publications. An example with its simulation is given for illustration of theoretical results.

Novel Results for Global Exponential Stability of Uncertain Systems with Interval Time-varying Delay

  • Liu, Yajuan;Lee, Sang-Moon;Kwon, Oh-Min;Park, Ju H.
    • Journal of Electrical Engineering and Technology
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    • v.8 no.6
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    • pp.1542-1550
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    • 2013
  • This paper presents new results on delay-dependent global exponential stability for uncertain linear systems with interval time-varying delay. Based on Lyapunov-Krasovskii functional approach, some novel delay-dependent stability criteria are derived in terms of linear matrix inequalities (LMIs) involving the minimum and maximum delay bounds. By using delay-partitioning method and the lower bound lemma, less conservative results are obtained with fewer decision variables than the existing ones. Numerical examples are given to illustrate the usefulness and effectiveness of the proposed method.

EXISTENCE AND GLOBAL EXPONENTIAL STABILITY OF POSITIVE ALMOST PERIODIC SOLUTIONS FOR A DELAYED NICHOLSON'S BLOWFLIES MODEL

  • Xu, Yanli
    • Journal of the Korean Mathematical Society
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    • v.51 no.3
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    • pp.473-493
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    • 2014
  • This paper concerns with a class of delayed Nicholson's blowflies model with a nonlinear density-dependent mortality term. Under appropriate conditions, we establish some criteria to ensure that the solutions of this model converge globally exponentially to a positive almost periodic solution. Moreover, we give some examples and numerical simulations to illustrate our main results.

ON GLOBAL EXPONENTIAL STABILITY FOR CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS

  • Kwon, O.M.;Park, Ju-H.;Lee, S.M.
    • Journal of applied mathematics & informatics
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    • v.26 no.5_6
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    • pp.961-972
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    • 2008
  • In this paper, we consider the global exponential stability of cellular neural networks with time-varying delays. Based on the Lyapunov function method and convex optimization approach, a novel delay-dependent criterion of the system is derived in terms of LMI (linear matrix inequality). In order to solve effectively the LMI convex optimization problem, the interior point algorithm is utilized in this work. Two numerical examples are given to show the effectiveness of our results.

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