Generalized projective synchronization of two coupled complex networks of different sizes

Abstract

Generalized projective synchronization of two coupled complex networks of different sizes *Li Ke-Zan(李科赞) a) † , He En(何 恩) a) , Zeng Zhao-Rong(曾朝蓉) b) , and Chi K. Tse(谢智刚) c)

Secure communication scheme analysis via complex networks

“…In addition, we study a new generalized projective synchronization (GPS) of coupled complex dynamical networks with different sizes via feedback control and impulsive control. By generalized projective synchronization, we mean that the states of nodes in each network can realize complete synchronization and the states of pair nodes from both networks can achieve projective synchronization. Since chaotic synchronization can be used for secure communication, this work may provide new insight for secure communication via projective synchronization on complex dynamical networks.…”

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

“…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. Amongst those types, projective synchronization has been widely researched [14][15][16] in recent years because it can obtain a faster communication with its proportional feature. Early research for complex network synchronization are most attention the synchronization of nodes within one complex network.…”

Identifying the interactions in a colored dynamical network

“…Many large-scale physical systems consisting of interactive individuals are usually modelled by complex dynamical networks, in which the nodes denote the individuals and the edges denote the interactions among them. [1][2][3][4][5][6][7][8][9][10] Generally, the interactions are denoted by the outer and inner coupling matrices. The outer coupling matrix denotes the topology and the coupling strength of the network, from which one can know whether a pair of nodes affect each other.…”