IJPAM: Volume 75, No. 2 (2012)

NEW STABILITY CRITERIA FOR TAKAGI-SUGENO
FUZZY HOPFIELD NEURAL NETWORKS

Choon Ki Ahn
Seoul National University of Science and Technology
172, Gongneung 2-Dong, Nowon-Gu, Seoul, 139-743, KOREA


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.

Received: November 24, 2011

AMS Subject Classification: 92B20, 34A07, 34D23

Key Words and Phrases: input/output-to-state stability (IOSS), Takagi-Sugeno (T-S) fuzzy Hopfield neural networks, linear matrix inequality (LMI)

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Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2012
Volume: 75
Issue: 2