Stability analysis of discrete‐time Markovian jump neural networks with time‐varying delays via a new summation inequality

Abstract This research focuses on the stability of discrete‐time Markovian jump neural networks with time‐varying delays. To this aim, a nonorthogonal free‐matrix‐based summation inequality (NFMSI) is proposed by constructing nonorthogonal polynomials with auxiliary scalars as well as auxiliary vectors. The NFMSI can avoid time‐varying delays in the denominator and prevent the loss of some coupling information compared to exiting summation inequalities. Then, an ameliorative stability criterion is derived by utilizing the NFMSI and other estimation method. Finally, the advantage of the obtained stability criterion is demonstrated by a few numerical examples.

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Publication Details

Journal
Asian Journal of Control
Published
2025-03-17
DOI
https://doi.org/10.1002/asjc.3626
Citations
2
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
2.97
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article

Stability analysis of discrete‐time Markovian jump neural networks with time‐varying delays via a new summation inequality

Ya‐Li Zhi, Fang Gao, Guozhi Yang, Wenbin Chen et al.
2 citations
Asian Journal of Control
Neural Networks Stability and Synchronization
2.97
article

Stability analysis of discrete‐time Markovian jump neural networks with time‐varying delays via a new summation inequality

Ya‐Li Zhi, Fang Gao, Guozhi Yang, Wenbin Chen, Yongjun Wu, Liuwen Chen
article en
2 citations

Abstract

Abstract This research focuses on the stability of discrete‐time Markovian jump neural networks with time‐varying delays. To this aim, a nonorthogonal free‐matrix‐based summation inequality (NFMSI) is proposed by constructing nonorthogonal polynomials with auxiliary scalars as well as auxiliary vectors. The NFMSI can avoid time‐varying delays in the denominator and prevent the loss of some coupling information compared to exiting summation inequalities. Then, an ameliorative stability criterion is derived by utilizing the NFMSI and other estimation method. Finally, the advantage of the obtained stability criterion is demonstrated by a few numerical examples.

Asian Journal of ControlVol. 27(6)
Anhui University (CN), Anhui Normal University (CN)
Openalex Percentile: Top 10%
Neural Networks Stability and Synchronization
2.97
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Stability analysis of discrete‐time Markovian jump neural networks with time‐varying delays via a new summation inequality — Ya‐Li Zhi, Fang Gao, et al. · Asian Journal of Control (2025) | TGRS Research Map | TGRS