Further results on robust delay-range-dependent stability criteria for uncertain neural networks with interval time-varying delay
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The problem of robust delay-range-dependent stability analysis of neural networks (NNs) with interval time-varying delay in a given range is investigated in this paper. The relationship between time-varying delay and its lower and upper bounds is taken into account when estimating the upper bound of the Lyapunov functional derivative. By defining a more general type of Lyapunov functionals, some new less conservative delay-dependent stability criteria are established in terms of linear matrix inequalities (LMIs), which can be computed and optimized easily. Meanwhile, the computational complexity of newly obtained stability conditions is reduced because fewer variables are involved. Finally, through four well-known numerical examples used in other literature, it will be shown that proposed stability criteria achieve the improvements over existing ones, as well as the effectiveness of the proposed idea.
KeywordsInterval time-varying delay linear matrix inequalities (LMIs) maximum allowable delay bound (MADB) neural networks (NNs)
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- Y. He, M. Wu, and J. H. She, “Delay-dependent exponential stability for delayed neural networks with time-varying delay,” IEEE Trans. on Circuits and Systems II-Express Briefs, vol. 53, no. 7, pp. 230–234, 2006.Google Scholar