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Wu, Z.G., Shi, P., Su, H. and Chu, J. (2013) Stochastic Synchronization of Markovian Jump Neural Networks with Time-Varying Delay Using Sampled Data. IEEE Transactions on Cybernetics, 43, 1796-1806.
https://doi.org/10.1109/TSMCB.2012.2230441

has been cited by the following article:

• TITLE: Nonstationary Filtering for Markov Jumping Systems with Fading Channel and Multiplicative Noises

  AUTHORS: Yang Zhan, Daijun Wei

  KEYWORDS: Markov Jumping System, l2 - l∞ Performance, Fading Channel, Nonstationary Filtering, Multiplicative Noises

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.9 No.4, April 2, 2021

  ABSTRACT: This paper studies the nonstationary filtering problem of Markov jump system underl2 - l∞performance. Due to the difference in propagation channels, signal strength and phase will inevitably change randomly and cause the waste of signals resources. In response to this problem, a channel fading model with multiplicative noise is introduced. And then a nonstationary filter, which receives signals more efficiently is designed. Meanwhile Lyapunov function is constructed for error analysis. Finally, the gain matrix for filtering is obtained by solving the matrix inequality, and the results showed that the nonstationary filter converges to the stable point more quickly than the traditional asynchronous filter, the stability of the designed filter is verified.