Exponential stability and periodicity of memristor-based recurrent neural networks with time-varying delays
2017 ◽
Vol 10
(02)
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pp. 1750027
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Keyword(s):
In this paper, the stability and periodicity of memristor-based neural networks with time-varying delays are studied. Based on linear matrix inequalities, differential inclusion theory and by constructing proper Lyapunov functional approach and using linear matrix inequality, some sufficient conditions are obtained for the global exponential stability and periodic solutions of memristor-based neural networks. Finally, two illustrative examples are given to demonstrate the results.
2015 ◽
Vol 742
◽
pp. 399-403
2007 ◽
Vol 17
(03)
◽
pp. 207-218
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2015 ◽
Vol 2015
◽
pp. 1-11
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2004 ◽
Vol 14
(09)
◽
pp. 3377-3384
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2011 ◽
Vol 204-210
◽
pp. 1549-1552
2013 ◽
Vol 330
◽
pp. 1045-1048
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Keyword(s):