Mean square exponential synchronization for a class of Markovian switching complex networks under feedback control and M-matrix approach

Adaptive exponential synchronization in mean square for Markovian jumping neutral-type coupled neural networks with time-varying delays by pinning control

“…Theorem 1 only gives a sufficient condition of mean square exponential synchronization of the neutral type neural network (1) by constructing a Lyapunov function. Actually, there have some other methods to reduce the conservatism of the obtained results such as delay-partition approach [38], small gain method [39] and so on. Besides these, we should construct reasonable Lyapunov functions, such that sufficient conditions have lower conservatism.…”

The Impact of Coupling Function on Finite‐Time Synchronization Dynamics of Multi‐Weighted Complex Networks with Switching Topology

“…During recent years, many researchers have paid close attention to synchronization dynamics problems of complex networks because synchronization dynamics is one of the most important collective behavior of complex networks [1][2][3] and many practical systems, including sensor network, communication network, neural networks, social network, and so on [4][5][6], can be modeled by complex networks. Therefore, many valuable and meaningful results for synchronization dynamics problems of complex networks have been obtained [7][8][9][10][11][12][13].…”

Projective synchronization between two delayed networks of different sizes with nonidentical nodes and unknown parameters

“…Synchronization [6][7] as an interesting and significant collective behavior of complex networks has been extensively studied. And various types of synchronization have been introduced, such as complete synchronization [8], projective synchronization [9][10], impulsive synchronization [11], cluster synchronization [12], Lag synchronization [13] and so on.…”