2016
DOI: 10.1016/j.neucom.2015.07.029
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Relaxed dissipativity criteria for memristive neural networks with leakage and time-varying delays

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Cited by 19 publications
(4 citation statements)
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“…So far, substantial important results on dissipativity have been obtained for MNNs. Unfortunately, the work in [27,28] only considered the leakage delay, while that in [29,30] considered additive time-varying delays, but not distribution delays. In fact, the leakage delay and multiple signal transmission delays coexist in the system of MNNs.…”
Section: Introductionmentioning
confidence: 99%
“…So far, substantial important results on dissipativity have been obtained for MNNs. Unfortunately, the work in [27,28] only considered the leakage delay, while that in [29,30] considered additive time-varying delays, but not distribution delays. In fact, the leakage delay and multiple signal transmission delays coexist in the system of MNNs.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, since 2008, its potential applications have become more and more popular in many aspects such as generation computer, powerful brain-like neural computer, and so on. There is no doubt that it has initiated the worldwide concern with the emergence of the memristor (see [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]). For the neural networks, the first job is considering whether they are stable or not.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, as far as we know, the passivity theory plays an important role in the analysis of the stability of dynamical systems, nonlinear control, and other areas. Thus, some researchers have investigated passivity or dissipativity criteria on MRNNs (see [14,16,[23][24][25][27][28][29][30]).…”
Section: Introductionmentioning
confidence: 99%
“…Over the past years, the study of time delay systems has received considerable attention, and a great number of research results on time delay systems exist in the literature. The stability of time delay systems is a fundamental problem because it is important in the synthesis and analysis of such neural network systems [ 3 , 5 , 24 , 25 ]. The exponential stability of stochastic BAM networks with mixed delays was discussed by Lyapunov theory [ 25 ].…”
Section: Introductionmentioning
confidence: 99%