Title of article
Robust exponential stability of uncertain fuzzy Cohen–Grossberg neural networks with time-varying delays
Author/Authors
Balasubramaniam، نويسنده , , P. and Ali، نويسنده , , M. Syed، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2010
Pages
11
From page
608
To page
618
Abstract
In this paper, the Takagi–Sugeno (T–S) fuzzy model representation is extended to the stability analysis for uncertain Cohen–Grossberg neural networks (CGNNs) with time-varying delays. A novel linear matrix inequality (LMI) based stability criterion is obtained by using Lyapunov functional theory to guarantee the exponential stability of uncertain CGNNs with time varying delays which are represented by T–S fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.
Keywords
Global exponential stability , Linear matrix inequality , Lyapunov functional , Time-varying delays , T–S fuzzy model , Cohen–Grossberg neural networks
Journal title
FUZZY SETS AND SYSTEMS
Serial Year
2010
Journal title
FUZZY SETS AND SYSTEMS
Record number
1601060
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