EconPapers    
Economics at your fingertips  
 

Dynamical behaviour analysis of delayed complex-valued neural networks with impulsive effect

Xiaohui Xu, Jiye Zhang and Jizhong Shi

International Journal of Systems Science, 2017, vol. 48, issue 4, 686-694

Abstract: This paper investigates the problem of the dynamical behaviours of a class of complex-valued neural networks with mixed time delays and impulsive effect. By separating the complex-valued neural networks into the real and the imaginary parts, the corresponding equivalent real-valued systems are obtained. Some sufficient conditions are derived for assuring the exponential stability of the equilibrium point of the system based on the vector Lyapunov function method and mathematical induction method. The obtained results generalise the existing ones. Finally, two numerical examples with simulations are given to demonstrate the feasibility of the proposed results.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2016.1206988 (text/html)
Access to full text is restricted to subscribers.

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:taf:tsysxx:v:48:y:2017:i:4:p:686-694

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2016.1206988

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst (chris.longhurst@tandf.co.uk).

 
Page updated 2024-12-29
Handle: RePEc:taf:tsysxx:v:48:y:2017:i:4:p:686-694