Abstract
In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2-L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix inequality (LMI). The proposed sets of criteria also guarantee exponential stability for T-S fuzzy Hopfield neural networks without external input.
Original language | English |
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Pages (from-to) | 2979-2986 |
Number of pages | 8 |
Journal | International Journal of Innovative Computing, Information and Control |
Volume | 9 |
Issue number | 7 |
Publication status | Published - 2013 |
Keywords
- Exponential L-L stability
- Linear matrix inequality (LMI)
- Matrix norm
- Takagi-Sugeno (T-S) fuzzy hopfield neural network
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Information Systems
- Computational Theory and Mathematics