DocumentCode
2395432
Title
Novel global exponential stability condition for discrete-time recurrent neural networks with random time-varying delays:
Author
Fattahi, Maryarn ; Momeni, Harnidreza
Author_Institution
Electr. Eng. Dept., Tarbiat Modares Univ., Tehran, Iran
fYear
2010
fDate
3-4 Nov. 2010
Firstpage
1
Lastpage
4
Abstract
In this paper, problem of stability for a class of discrete-time recurrent neural networks (DRNNs) with time-varying delay is considered. By employing the Lyapunov-Krasovskii function, a new condition for stability of time-delayed system is proposed. Result developed is in the term of linear matrix inequality (LMI) which can be easily checked by LMI Control toolbox. Furthermore, numerical examples are given to confirm the validity of the obtained approach.
Keywords
Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; random processes; time-varying systems; DRNN; Lyapunov-Krasovskii function; discrete-time recurrent neural networks; global exponential stability; linear matrix inequality; random time-varying delays; time-delayed system; Power capacitors; Lyapunov-Krasovskii function; discrete-time recurrent neural networks; linear matrix inequality;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering (ICBME), 2010 17th Iranian Conference of
Conference_Location
Isfahan
Print_ISBN
978-1-4244-7483-7
Type
conf
DOI
10.1109/ICBME.2010.5705031
Filename
5705031
Link To Document