Input-to-state stability of recurrent neural networks with time-varying delays and Markovian switching

Yong Xu Yong Xu,Song Zhu

doi:10.1109/ccdc.2012.6243023

Input-to-state stability of recurrent neural networks with time-varying delays and Markovian switching

Yong Xu Yong Xu, Song Zhu

https://doi.org/10.1109/ccdc.2012.6243023

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Publication Date: May 1, 2012

Affiliation: Central South University, China University of Mining and Technology

#Stability Of Recurrent Neural Networks #Input-to-state Stability + Show 8 more

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Abstract

This paper presents an algebraic criterion for the input-to-state stability (ISS) of recurrent neural networks with Markovian switching. The criterion is easy to be verified with the connection weights. A numerical example is given to demonstrate the effectiveness of the proposed criteria.

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