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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Finite-Horizon $l_2-l_infty$ Synchronization for Time-Varying Markovian Jump Neural Networks Under Mixed-Type Attacks: Observer-Based Case
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Finite-Horizon $l_2-l_infty$ Synchronization for Time-Varying Markovian Jump Neural Networks Under Mixed-Type Attacks: Observer-Based Case

机译:Unitite-Horizo​​ n <内联 - 公式> $ l_2-l_ infty $

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摘要

This paper studies the synchronization issue of time-varying Markovian jump neural networks (NNs). The denial-of-service (DoS) attack is considered in the communication channel connecting master NNs and slave NNs. An observer is designed based on the measurements of master NNs transmitted over this unreliable channel to estimate their states. The deception attack is used to destroy the controller by changing the sign of the control signal. Then, the mixed-type attacks are expressed uniformly, and a synchronization error system is established using this function. A finite-horizon l(2) - l(infinity) performance is proposed, and sufficient conditions are derived to ensure that the synchronization error system satisfies this performance. The controllers are then obtained by a recursive linear matrix inequality algorithm. At last, a simulation result to show the feasibility of the developed results is given.
机译:本文研究了时变马尔维亚跳跃神经网络(NNS)的同步问题。在连接主题NNS和SLAVE NNS的通信信道中考虑拒绝服务(DOS)攻击。基于在该不可靠的信道上传输的主NNS的测量值来设计观察者以估计其状态。欺骗攻击用于通过改变控制信号的符号来破坏控制器。然后,混合型攻击均匀表示,并且使用此功能建立同步误差系统。提出了有限地平线L(2) - L(Infinity)性能,推导出充分的条件,以确保同步误差系统满足这种性能。然后通过递归线性矩阵不等式算法获得控制器。最后,给出了仿真结果以显示发达结果的可行性。

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