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Neural Processing Letters

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20-08-2021

Input-to-State Stability for Stochastic Delay Neural Networks with Markovian Switching

Authors: Yumei Fan, Huabin Chen

Published in: Neural Processing Letters | Issue 6/2021

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Abstract

In this paper, some problems on the input-to-state stability, integral input-to-state stability, and stochastic input-to-state stability of stochastic non-autonomous neural networks with time-varying delay and Markovian switching are investigated. By using the generalized integral inequality, the Lyapunov function approach and the stochastic analysis theory, the input-to-state stability, integral input-to-state stability, and stochastic input-to-state stability for such neural networks are discussed when the time-varying delay is a bounded function. The integral input-to-state stability and stochastic input-to-state stability are also implied. One example is given to illustrate the derived theoretical result.

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Title: Input-to-State Stability for Stochastic Delay Neural Networks with Markovian Switching
Authors: Yumei Fan
Huabin Chen
Publication date: 20-08-2021
Publisher: Springer US
Published in: Neural Processing Letters / Issue 6/2021
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-021-10605-8

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