Quasi‐projective and finite‐time synchronization of delayed fractional‐order BAM neural networks via quantized control

Abstract

This paper deals with the problems of quasi-projective synchronization (QPS) and finite-time synchronization (FTS) for a kind of delayed fractional-order BAM neural networks (DFOBAMNNs). In order to reach the goals of synchronization and more accurately gauge of settling time and error level, several fresh quantized controllers are structured to make the utmost of confined communication resources. Then, based on the finite-time theorem, quantized control strategy, Lyapunov function theory and properties of Mittag-Leffler function as well as inequality analysis techniques, some plentiful criteria are formed to set up a relation between control gains and quantization parameters. In addition, the corresponding error bound of QPS and guages of the settling time on FTS are also given. Finally, a few numerical examples are introduced to validate the effectiveness of the presented control protocols.

Stochastic synchronization of Kuramoto-oscillator network with pinning control

“…Unlike most existing studies, it extended the conditions satisfied by the nodes in the system and increased the range of practical applications. Considering the numerous advantages of FT synchronization, researchers have applied it to neural network synchronization [22], and multi-layer network synchronization [23].…”