2010
DOI: 10.1016/j.amc.2010.05.037
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Projective synchronization of different chaotic time-delayed neural networks based on integral sliding mode controller

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Cited by 69 publications
(45 citation statements)
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“…then the response neural network (35) can globally asymptotically synchronize the drive neural network (34), and the gain matrix K can be designed as…”
Section: Resultsmentioning
confidence: 99%
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“…then the response neural network (35) can globally asymptotically synchronize the drive neural network (34), and the gain matrix K can be designed as…”
Section: Resultsmentioning
confidence: 99%
“…The provided conditions are expressed in terms of LMI, and are dependent on the discrete and distributed time delays as well as leakage delay. Differing from the results in [33][34][35], the main contributions of this study are to investigate the effect of the leakage delay on the synchronization of two nonidentical chaotic neural networks with discrete and distributed time-varying delays as well as leakage delay and to propose an integral sliding mode control approach to solving it.…”
Section: Introductionmentioning
confidence: 99%
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“…Since the discovery of chaos synchronization, different approaches have been proposed to achieve it, such as PC method [24], active control method [1,71,12,66], adaptive control method [47,48,38,67], backstepping control method [53,28,29,52,30,68], sliding mode control method [73,51,56,69,23,63], etc.…”
Section: Introductionmentioning
confidence: 99%