Abstract
This article aims to study a class of discontinuous fuzzy inertial Cohen–Grossberg neural networks (DFICGNNs) with discrete and distributed time-delays. First of all, in order to deal with the discontinuities by the differential inclusion theory, based on a generalized variable transformation including two tunable variables, the mixed time-varying delayed DFICGNN is transformed into a first-order differential system. Then, by constructing a modified Lyapunov–Krasovskii functional concerning with the mixed time-varying delays and designing a delayed feedback control law, delay-dependent criteria formulated by algebraic inequalities are derived for guaranteeing the finite-time stabilization (FTS) for the addressed system. Moreover, the settling time is estimated. Some related stability results on inertial neural networks is extended. Finally, two numerical examples are carried out to verify the effectiveness of the established results.
Highlights
1.1 Previous worksIn 1986, Babcock et al [3] proposed the inertial neural networks (INNs) for the first time
The concept of finite-time stabilization (FTS) proposed by Haimo [6] means that the solutions of the system reach the equilibrium point in finite time
Based on the pioneer works and addressed two key purposes mentioned above, in this paper, we aim to investigate the FTS of DFICGNNs with mixed time delays via discontinuous state-feedback controllers
Summary
In 1986, Babcock et al [3] proposed the inertial neural networks (INNs) for the first time. It is meaningful to further propose a new framework and study the FTS of the discontinuous INNs with mixed time-varying delays and derive some new delaydependent criteria to ensure the FTS of discontinuous INNs with mixed time-varying delays During the past several years, based on the pioneer work of Yang and Yang [25] in 1996, stability analysis of fuzzy neural networks with delays were extensively considered by researchers; see [10,11,12, 18] and the references therein.
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