Open AccessMatrix Measure Strategies for Stabilization of Delayed Inertial Neural Networks via Intermittent Control
Author(s) -
Xuan Chen,
Guixian Cheng,
Wenjun Xiao
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3127147
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In this paper, stabilization control of a class of delayed inertial neural networks (INN) is investigated. Employing matrix measure method and two Halanay-type inequalities, some succinct stabilization criteria in terms of algebraic inequalities are derived for the INN with time-varying delays under periodically intermittent control (PIMC) strategy. Moreover, more precise results are obtained to stabilize the INN with time-invariant delays by using comparison principle. Specifically, the criteria of matrix measure form proposed in this paper can be converted into LMI-type condition for the case of 2-norm, which provides a bridge between the matrix-measure method and the Lyapunov function method. Finally, two numerical examples validate the efficacy of the derived results. The comparative research shows that the proposed methods generalize and develop some known results.