Intermittent Control for Synchronization of Markov Jump Inertial Neural Networks with Reaction–Diffusion Terms via Non-reduced-Order Method

• Published in: Circuits, systems, and signal processing Vol. 42; no. 1; pp. 199 - 215
• Main Authors: Hu, Dongxiao, Song, Xiaona, Li, Xingru, Ma, Jianwei
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2023; Springer Nature B.V
• Subjects: Circuits; Circuits and Systems; Controllers; Diffusion; Electrical Engineering; Electronics and Microelectronics; Engineering; Instrumentation; Liapunov direct method; Methods; Neural networks; Sampled data; Signal processing; Signal,Image and Speech Processing; Substitution reactions; Synchronism; Aperiodically intermittent controller; Spatially sampled data; Synchronization; Reaction–diffusion; Markov jump inertial neural networks; Non-reduced order
• ISSN: 0278-081X; 1531-5878
• DOI: 10.1007/s00034-022-02132-1

This paper concentrates on designing an aperiodically intermittent controller for synchronization of Markov jump inertial neural networks (MJINNs) with reaction–diffusion terms. Unlike the traditional reduced-order variable substitution method, the synchronization for MJINNs is studied directly using a non-reduced-order method. Besides, an aperiodic intermittent controller with spatially sampled data, which is intermittent in time and sampled data in space, is constructed under the consideration of the limited communication bandwidth. Furthermore, based on the Lyapunov direct method and several inequality techniques, the synchronization criteria of MJINNs under the proposed controller are derived. Finally, the proposed approach’s effectiveness is illustrated by using a numerical example.