In this work,an H_(∞)/passive-based secure synchronization control problem is investigated for continuous-time semi-Markov neural networks subject to hybrid attacks,in which hybrid attacks are the combinations of den...In this work,an H_(∞)/passive-based secure synchronization control problem is investigated for continuous-time semi-Markov neural networks subject to hybrid attacks,in which hybrid attacks are the combinations of denial-of-service attacks and deception attacks,and they are described by two groups of independent Bernoulli distributions.On this foundation,via the Lyapunov stability theory and linear matrix inequality technology,the H_(∞)/passive-based performance criteria for semi-Markov jump neural networks are obtained.Additionally,an activation function division approach for neural networks is adopted to further reduce the conservatism of the criteria.Finally,a simulation example is provided to verify the validity and feasibility of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.62103005,62173001,and 62273006the Natural Science Foundation of Anhui Provincial Natural Science Foundation under Grant No.2108085QF276+3 种基金the Natural Science Foundation for Distinguished Young Scholars of Higher Education Institutions of Anhui Province under Grant No.2022AH020034the Natural Science Foundation for Excellent Young Scholars of Higher Education Institutions of Anhui Province under Grant No.2022AH030049,2023AH030030,2022AH030049the Major Technologies Research and Development Special Program of Anhui Province under Grant No.202003a05020001the Key Research and Development Projects of Anhui Province under Grant No.202104a05020015。
文摘In this work,an H_(∞)/passive-based secure synchronization control problem is investigated for continuous-time semi-Markov neural networks subject to hybrid attacks,in which hybrid attacks are the combinations of denial-of-service attacks and deception attacks,and they are described by two groups of independent Bernoulli distributions.On this foundation,via the Lyapunov stability theory and linear matrix inequality technology,the H_(∞)/passive-based performance criteria for semi-Markov jump neural networks are obtained.Additionally,an activation function division approach for neural networks is adopted to further reduce the conservatism of the criteria.Finally,a simulation example is provided to verify the validity and feasibility of the proposed method.
