Enhanced stability criteria of neural networks with time-varying delays via a generalized free-weighting matrix integral inequality |
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| Authors: | MJ Park SH Lee OM Kwon JH Ryu |
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| Institution: | 1. Center for Global Converging Humanities, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Republic of Korea;2. School of Electrical Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju 28644, Republic of Korea;3. Electronics and Telecommunications Research Institute, 176-11 Cheomdan Gwagi-ro, Buk-gu, Gwangju 61012, Republic of Korea |
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| Abstract: | This paper deals with the problem of delay-dependent stability analysis for neural networks with time-varying delays. First, by constructing an augmented Lyapunov–Krasovskii functional and utilizing a generalized free-weighting matrix integral inequality, an improved stability criterion for the concerned network is derived in terms of linear matrix inequalities. Second, by considering a marginal augmented vector and modifying a Lyapunov–Krasovsii functional, a further enhanced stability criterion is presented. Third, a less conservative stability condition in which a relaxed inequality related to activation functions is added is introduced. Finally, three numerical examples are included to illustrate the advantage and validity of the proposed criteria. |
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| Keywords: | Corresponding authors |
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