Abstract
In this paper, new stability criteria are derived for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks via the input/output-to-state stability (IOSS) approach. Based on matrix norm and linear matrix inequality (LMI), these stability criteria guarantee input/output-to-state stability for external input vector. Moreover, the criteria for asymptotic stability of T-S fuzzy Hopfield neural networks without external input vector are presented.
| Original language | English |
|---|---|
| Pages (from-to) | 237-246 |
| Number of pages | 10 |
| Journal | International Journal of Pure and Applied Mathematics |
| Volume | 75 |
| Issue number | 2 |
| Publication status | Published - 2012 Mar 12 |
| Externally published | Yes |
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Keywords
- Input/output-to-state stability (IOSS)
- Linear matrix inequality (LMI)
- Takagi-Sugeno (T-S) fuzzy Hopfield neural networks
ASJC Scopus subject areas
- Mathematics(all)
- Applied Mathematics
Cite this
New stability criteria for Takagi-Sugeno fuzzy Hopfield neural networks. / Ahn, Choon Ki.
In: International Journal of Pure and Applied Mathematics, Vol. 75, No. 2, 12.03.2012, p. 237-246.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - New stability criteria for Takagi-Sugeno fuzzy Hopfield neural networks
AU - Ahn, Choon Ki
PY - 2012/3/12
Y1 - 2012/3/12
N2 - In this paper, new stability criteria are derived for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks via the input/output-to-state stability (IOSS) approach. Based on matrix norm and linear matrix inequality (LMI), these stability criteria guarantee input/output-to-state stability for external input vector. Moreover, the criteria for asymptotic stability of T-S fuzzy Hopfield neural networks without external input vector are presented.
AB - In this paper, new stability criteria are derived for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks via the input/output-to-state stability (IOSS) approach. Based on matrix norm and linear matrix inequality (LMI), these stability criteria guarantee input/output-to-state stability for external input vector. Moreover, the criteria for asymptotic stability of T-S fuzzy Hopfield neural networks without external input vector are presented.
KW - Input/output-to-state stability (IOSS)
KW - Linear matrix inequality (LMI)
KW - Takagi-Sugeno (T-S) fuzzy Hopfield neural networks
UR - http://www.scopus.com/inward/record.url?scp=84857891462&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857891462&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84857891462
VL - 75
SP - 237
EP - 246
JO - International Journal of Pure and Applied Mathematics
JF - International Journal of Pure and Applied Mathematics
SN - 1311-8080
IS - 2
ER -