Title :
Novel stability criteria of T-S fuzzy hopfield neural networks with time-varying delays and uncertainties
Author :
Zhou, C.G. ; Zeng, X.Q. ; Yu, J.J.
Author_Institution :
Inst. of Intell. Sci. & Technol., Hohai Univ., Nanjing, China
Abstract :
The problem of asymptotic stability for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks with time-varying delays is studied in this paper. Based on the Lyapunov functional method, new delay-dependent stability criteria are derived in terms of Linear Matrix Inequalities (LMIs) that can be calculated easily by the LMI Toolbox in MATLAB. The proposed approach does not involve free weighting matrices and can provide less conservative results than some existing ones. Besides, numerical examples are given to show the effectiveness of the proposed approach.
Keywords :
Hopfield neural nets; Lyapunov methods; asymptotic stability; delay systems; fuzzy neural nets; linear matrix inequalities; stability criteria; time-varying systems; LMI toolbox; Lyapunov functional method; MATLAB; T-S fuzzy Hopfield neural networks; Takagi-Sugeno fuzzy Hopfield neural networks; asymptotic stability; delay-dependent stability criteria; free weighting matrices; linear matrix inequality; time-varying delays; uncertainty; Biological neural networks; Delays; Hopfield neural networks; Stability criteria; Time-varying systems; Uncertainty; Hopfield neural networks; T-S fuzzy model; asymptotic stability; time-varying delay; uncertainty;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889410
