Abstract
This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.
| Original language | English |
|---|---|
| Pages (from-to) | 237-246 |
| Number of pages | 10 |
| Journal | Neural Processing Letters |
| Volume | 27 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2008 Jun 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Neuroscience(all)
- Computer Networks and Communications
- Artificial Intelligence
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A delay-dependent approach to passivity analysis for uncertain neural networks with time-varying Delayd. / Lu, Chien-Yu; Tsai, Hsun Heng; Su, Te Jen; Tsai, Jason Sheng Hong; Liao, Chin-Wen.
In: Neural Processing Letters, Vol. 27, No. 3, 01.06.2008, p. 237-246.Research output: Contribution to journal › Article
TY - JOUR
T1 - A delay-dependent approach to passivity analysis for uncertain neural networks with time-varying Delayd
AU - Lu, Chien-Yu
AU - Tsai, Hsun Heng
AU - Su, Te Jen
AU - Tsai, Jason Sheng Hong
AU - Liao, Chin-Wen
PY - 2008/6/1
Y1 - 2008/6/1
N2 - This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.
AB - This paper deals with the problem of passivity analysis for neural networks with time-varying delay, which is subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. Delay-dependent passivity condition is proposed by using the free-weighting matrix approach. These passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness of the proposed criteria.
UR - http://www.scopus.com/inward/record.url?scp=42449161839&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=42449161839&partnerID=8YFLogxK
U2 - 10.1007/s11063-008-9072-2
DO - 10.1007/s11063-008-9072-2
M3 - Article
AN - SCOPUS:42449161839
VL - 27
SP - 237
EP - 246
JO - Neural Processing Letters
JF - Neural Processing Letters
SN - 1370-4621
IS - 3
ER -