Title of article
Some new results on stability of Takagi–Sugeno fuzzy Hopfield neural networks
Author/Authors
Ahn، نويسنده , , Choon Ki، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
12
From page
100
To page
111
Abstract
In this paper, we propose some new results on stability properties of Takagi–Sugeno fuzzy Hopfield neural networks with time-delay. Based on Lyapunov stability theory, a new learning law is derived to guarantee passivity and asymptotical stability of Takagi–Sugeno fuzzy Hopfield neural networks. Furthermore, a new condition for input-to-state stability (ISS) is established. Illustrative examples are given to demonstrate the effectiveness of the proposed results.
Keywords
Learning , Neuro-fuzzy systems , passivity , Input-to-state stability (ISS) , Lyapunov stability theory
Journal title
FUZZY SETS AND SYSTEMS
Serial Year
2011
Journal title
FUZZY SETS AND SYSTEMS
Record number
1601359
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