EconPapers    
Economics at your fingertips  
 

Mean Square Exponential Stability of Stochastic Complex-Valued Neural Networks with Mixed Delays

Xiaohui Xu, Jibin Yang and Yanhai Xu

Complexity, 2019, vol. 2019, 1-20

Abstract:

This paper investigates the mean square exponential stability problem of a class of complex-valued neural networks with stochastic disturbance and mixed delays including both time-varying delays and continuously distributed delays. Under different assumption conditions concerning stochastic disturbance term from the existing ones, some sufficient conditions are derived for assuring the mean square exponential stability of the equilibrium point of the system based on the vector Lyapunov function method and differential-integral theorem. The obtained results not only generalize the existing ones, but also reduce the conservatism of the previous stability results about complex-valued neural networks with stochastic disturbances. Two numerical examples with simulation results are given to verify the feasibility of the proposed results.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2019/3429326.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2019/3429326.xml (text/xml)

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:hin:complx:3429326

DOI: 10.1155/2019/3429326

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().

 
Page updated 2025-03-19
Handle: RePEc:hin:complx:3429326