Asymptotical and adaptive synchronization of Cohen–Grossberg neural networks with heterogeneous proportional delays

Pinning synchronization of complex delayed dynamical networks via generalized intermittent adaptive control strategy

“…Then, based on Theorems 1 and 2, the following Corollaries 3 and 4 are immediately obtained, respectively. (27) satisfying (28) and (29), if there exist positive constants , , l 1 , l 2 such that…”

“…It is well known that adaptive control strategy is designed under control objective in the light of the characteristics of considered system. [27][28][29][30] The strong point of adaptive control is that the control parameters can automatically adjust themselves according to some proper updating laws. However, a typical real-world complex dynamical network usually consists of a great many of interconnected nodes.…”

Finite-Time Synchronization of Multi-Linked Memristor-Based Neural Networks With Mixed Time-Varying Delays

“…In general, the synchronization issue of MNNs can be transformed into the stabilization issue of MNNs. Many scholars have studied the synchronization of MNNs, and many excellent kinds of synchronization and stabilization have been proposed, such as lag synchronization [24]- [26], exponential synchronization [27]- [30], decay synchronization [31], [32], asymptotic synchronization [33], [34], finite-time synchronization [35]- [37], etc. And many significant and excellent results have been reported.…”

Almost surely asymptotic synchronization for stochastic neural networks of neutral type with Markovian jumping parameters

“…In order to achieve this purpose, a large number of approaches have been proposed for the synchronization of chaotic systems in the literature, [1][2][3][4][5][6][7][8][9] such as adaptive control method, 1,2,9 impulsive control method, 3 feedback control method, 4 and sliding mode control method. 5 Recently, since synchronization of stochastic neural networks plays an important role in fundamental science and technological practice, it has attracted much attention of researchers and many results of research have been reported in the literature (see other works [9][10][11][12][13][14][15][16][17][18][19] and the references therein). Wang et al 10 and Zhang et al 11,12 considered the problem of exponential synchronization for stochastic neural networks with time-varying delays.…”

“…For instance, Zheng and Xian 13 established several novel delay-dependent conditions to assure the globally asymptotical synchronization for chaotic memristor-based neural networks with time-varying delays. Jia et al 14 obtained some sufficient conditions to ensure the asymptotic synchronization in the mean square for Cohen-Grossberg neural networks with heterogeneous proportional delays via using the adaptive control strategy. Gao et al 15 derived several sufficient conditions to guarantee the globally asymptotic synchronization for stochastic memristor-based neural networks with noise disturbance.…”