2009
DOI: 10.1016/j.nahs.2008.10.006
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Impulsive control of a hysteresis cellular neural network model

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Cited by 10 publications
(6 citation statements)
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“…Ƒ Figure 3. Phase portrait of Gui chaotic strange attractor of system (2) For the purpose of synchronization, we introduce the response system that is driven by (1) via a set of signals …”
Section: Preliminaries and Problem Formulationmentioning
confidence: 99%
See 1 more Smart Citation
“…Ƒ Figure 3. Phase portrait of Gui chaotic strange attractor of system (2) For the purpose of synchronization, we introduce the response system that is driven by (1) via a set of signals …”
Section: Preliminaries and Problem Formulationmentioning
confidence: 99%
“…Recently, the issue of controlled synchronization in complex dynamical networks has become a rather significant topic in both theoretical research and practical applications [1][2][3]. It is known that in theory and practice, impulsive control has been widely used to stabilize and synchronize chaotic systems.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, many researchers focused their attention on impulsive control (impulsive stabilization) of delayed neural networks. This is quite different from the cases of impulsive perturbation, which is a type of robustness problem, and some attractive results have been presented in the literature, for example [30][31][32][33][34][35][36][37][38][39][40][41]. The main idea of impulsive control in neural networks is to introduce an impulse input into the topological structure of the networks and then control the states of systems.…”
Section: Introductionmentioning
confidence: 99%
“…In 16 the authors investigated the optimal harvesting policy for an ecosystem with impulsive harvest. For some recent references on different control strategies, including impulsive control, we refer the reader to 13,[19][20][21][22][23][24][25][26] We say that system 1.1 -1.2 is exactly controllable in the time T > 0 if for any x 0 , x 1 there exists a control u such that a solution x of 1.1 -1.2 satisfies x 0 x 0 , x T x 1 . Of course, we specify below the space of solutions and controls.…”
Section: Introductionmentioning
confidence: 99%