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Adaptive Exponential State Estimation for Markovian Jumping Neural Networks with Multi-delays and Levy Noises

机译:具有多时滞和征费的马尔可夫跳跃神经网络的自适应指数状态估计

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摘要

This paper discusses the adaptive exponential state estimation problem of neutral-type neural networks with multi-delays and Levy noises. The M-matrix method being different from other methods, such as the LMIs method, has been applied to deal with the problem. According to the M-matrix method, some state estimation criteria for neural networks concerning neutral-type delays and no neutral-type delays are acquired to ensure the adaptive exponential estimation. Finally, a simulation example is offered to show the advantages of the theoretical results.
机译:本文讨论了具有多时滞和利维噪声的中立型神经网络的自适应指数状态估计问题。与其他方法(例如LMIs方法)不同的M矩阵方法已用于解决该问题。根据M矩阵方法,获取了一些关于神经网络的中立型时延和无中立型时延的状态估计准则,以确保自适应指数估计。最后,提供了一个仿真实例来说明理论结果的优势。

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