Algorithm

Control (management)

Discrete mathematics

Convergence (economics)

Economics

Computer science

Social connectedness

Digraph

Psychology

Mathematics

Strongly connected component

Psychotherapist

Synchronization (alternating current)

Artificial intelligence

Combinatorics

Economic growth

Topology (electrical circuits)

Control theory (sociology)

Artificial neural network

Fuzzy Sets and Systems

In this paper, the finite-time synchronization problem for multi-coupling fuzzy cellular neural networks (FCNNs) with stochastic perturbations and mixed delays is addressed. Compared with exponential synchronization and asymptotic synchronization in existing literature, finite-time synchronization of stochastic FCNNs is studied for the first time, which is of better significance. Combining graph-theoretical technique and Lyapunov method, under the framework of feedback control, some finite-time synchronization conditions are derived. Besides, from the perspective of the connectedness of FCNNs, we just demand at least one directed path on the digraph between different vertices in networks, instead of each sub-network. Then, the convergence time is explicitly proposed, which is connected with the parameters of control and topological structure of networks. Eventually, a numerical example is also carried out to demonstrate the practicability and validity of our proposed results. Furthermore, a secure communication synchronization problem is presented to illustrate the effectiveness of the obtained results.

Finite-time synchronization of multi-coupling stochastic fuzzy neural networks with mixed delays via feedback control