%0 Journal Article
	%A Zixin Liu and  Shu Lü and  Shouming Zhong and  Mao Ye
	%D 2010
	%J International Journal of Mathematical and Computational Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 43, 2010
	%T Improved Robust Stability Criteria for Discrete-time Neural Networks
	%U https://publications.waset.org/pdf/12962
	%V 43
	%X In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

	%P 759 - 764