Passivity-based synchronization for Markov switched neural networks with time delays and the inertial term

Tian Fang, Shiyu Jiao, Dongmei Fu and Lei Su

Applied Mathematics and Computation, 2021, vol. 394, issue C

Abstract: The passivity-based synchronization issue of Markov switched inertial neural networks with time delays is addressed in this work. Different from many articles, the influence of inertial term on neural network is taken into account, namely, the second-order derivative of the system model is emphasized. For this issue, the second-order differential equations are processed to establish the first-order ones by means of the variable transformation. Next, under the framework of drive-response, a mode dependent feedback controller is designed to implement passive synchronization of Markov switched inertial neural networks. Meanwhile, by an optimized inequality technique and Lyapunov stability theory, some sufficient conditions are established. Ultimately, through a comparative example displayed, the effectiveness and superiority of the results derived can be fully illustrated.

Keywords: Markov switched neural networks; Inertial neural networks; Passivity-based synchronization; Time delays (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300320307396
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:394:y:2021:i:c:s0096300320307396

DOI: 10.1016/j.amc.2020.125786

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().