Hybrid-driven-based H∞ filter design for neural networks subject to deception attacks

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摘要

This paper investigates the problem of H∞ filter design for neural networks with hybrid triggered scheme and deception attacks. In order to make full use of the limited network resources, a hybrid triggered scheme is introduced, in which the switching between the time triggered scheme and the event triggered scheme obeys Bernoulli distribution. By considering the effect of hybrid triggered scheme and deception attacks, a mathematical model of H∞ filtering error system is constructed. The sufficient conditions that can ensure the stability of filtering error system are given by using Lyapunov stability theory and linear matrix inequality (LMI) techniques. Moreover, the explicit expressions are provided for the designed filter parameters that is in terms of LMIs. Finally, a numerical example is employed to illustrate the design method.

论文关键词:Neural networks,Hybrid triggered scheme,H∞ filter design,Deception attacks

论文评审过程:Received 28 May 2017, Revised 2 August 2017, Accepted 6 September 2017, Available online 10 October 2017, Version of Record 10 October 2017.

论文官网地址:https://doi.org/10.1016/j.amc.2017.09.007