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Stochastic stability analysis for delayed neural networks of neutral type with Markovian jump parameters

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  • Lou, Xuyang
  • Cui, Baotong

Abstract

In this paper, the problem of stochastic stability for a class of delayed neural networks of neutral type with Markovian jump parameters is investigated. The jumping parameters are modelled as a continuous-time, discrete-state Markov process. A sufficient condition guaranteeing the stochastic stability of the equilibrium point is derived for the Markovian jumping delayed neural networks (MJDNNs) with neutral type. The stability criterion not only eliminates the differences between excitatory and inhibitory effects on the neural networks, but also can be conveniently checked. The sufficient condition obtained can be essentially solved in terms of linear matrix inequality. A numerical example is given to show the effectiveness of the obtained results.

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  • Lou, Xuyang & Cui, Baotong, 2009. "Stochastic stability analysis for delayed neural networks of neutral type with Markovian jump parameters," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2188-2197.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:5:p:2188-2197
    DOI: 10.1016/j.chaos.2007.06.114
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    References listed on IDEAS

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    1. Lou, Xuyang & Cui, Baotong, 2007. "Boundedness and exponential stability for nonautonomous cellular neural networks with reaction–diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 33(2), pages 653-662.
    2. Lou, Xuyang & Cui, Baotong, 2007. "Absolute exponential stability analysis of delayed bi-directional associative memory neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 695-701.
    3. Singh, Vimal, 2007. "On global robust stability of interval Hopfield neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 33(4), pages 1183-1188.
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    1. R. Sakthivel & R. Raja & S. M. Anthoni, 2013. "Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 251-273, July.
    2. Rathinasamy, Anandaraman & Mayavel, Pichamuthu, 2023. "The balanced split step theta approximations of stochastic neutral Hopfield neural networks with time delay and Poisson jumps," Applied Mathematics and Computation, Elsevier, vol. 455(C).
    3. R. Sakthivel & R. Raja & S. M. Anthoni, 2011. "Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses," Journal of Optimization Theory and Applications, Springer, vol. 150(1), pages 166-187, July.
    4. Luan, Xiaoli & He, Shuping & Liu, Fei, 2009. "Neural network-based robust fault detection for nonlinear jump systems," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 760-766.
    5. Liu, Yan & Yu, Pinrui & Chu, Dianhui & Su, Huan, 2019. "Stationary distribution of stochastic Markov jump coupled systems based on graph theory," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 188-195.

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