Synchronization of competitive neural networks with different time scales

Xuyang Lou and Baotong Cui

Physica A: Statistical Mechanics and its Applications, 2007, vol. 380, issue C, 563-576

Abstract: In this paper, the exponential synchronization problem for a class of competitive neural networks is investigated. Moreover, without assuming the active functions to be differentiable and bounded, some exponential synchronization criteria are devised by Lyapunov functionals, linear matrix inequality (LMI) approach, the Leibniz–Newton formula. The conditions are less conservative than existing ones reported in the literature for delayed neural networks. The applicability of the conditions are validated by an illustrative example.

Keywords: Competitive neural networks; Synchronization; Leibniz–Newton formula; Lyapunov functional; Time scales (search for similar items in EconPapers)
Date: 2007
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/S0378437107001768
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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:phsmap:v:380:y:2007:i:c:p:563-576

DOI: 10.1016/j.physa.2007.02.088

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().