Abstract
This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.
| Original language | English |
|---|---|
| Pages (from-to) | 216-232 |
| Number of pages | 17 |
| Journal | International Journal of Electronics |
| Volume | 102 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2015 Feb 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
Cite this
}
Robust passivity analysis for discrete-time recurrent neural networks with mixed delays. / Huang, Chuan Kuei; Shu, Yu Jeng; Chang, Koan Yuh; Shou, Ho Nien; Lu, Chien Yu.
In: International Journal of Electronics, Vol. 102, No. 2, 01.02.2015, p. 216-232.Research output: Contribution to journal › Article
TY - JOUR
T1 - Robust passivity analysis for discrete-time recurrent neural networks with mixed delays
AU - Huang, Chuan Kuei
AU - Shu, Yu Jeng
AU - Chang, Koan Yuh
AU - Shou, Ho Nien
AU - Lu, Chien Yu
PY - 2015/2/1
Y1 - 2015/2/1
N2 - This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.
AB - This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.
UR - http://www.scopus.com/inward/record.url?scp=84911452751&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911452751&partnerID=8YFLogxK
U2 - 10.1080/00207217.2014.896043
DO - 10.1080/00207217.2014.896043
M3 - Article
AN - SCOPUS:84911452751
VL - 102
SP - 216
EP - 232
JO - International Journal of Electronics
JF - International Journal of Electronics
SN - 0020-7217
IS - 2
ER -