Stability analysis of higher-order recurrent neural networks with multiple delays

Global asymptotic stability problem for a class of recurrent neural networks with both high-order term and discrete delays has been studied based on delay-matrix decomposition method and linear matrix inequality technique. The proposed stability criterion extends the existing stability for the multi...

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Bibliographic Details
Main Authors: Zhanshan Wang, Zhenwei Liu, Tao Liu
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Asymptotic stability
Delay
Linear matrix inequalities
Recurrent neural networks
Stability criteria
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Summary:Global asymptotic stability problem for a class of recurrent neural networks with both high-order term and discrete delays has been studied based on delay-matrix decomposition method and linear matrix inequality technique. The proposed stability criterion extends the existing stability for the multiple delayed recurrent neural networks with higher order terms. Compared with the existing results, our results are new and easy to check.
DOI:10.1109/ICICIP.2010.5565281