Non-Fragile H<sub>&#x221E;</sub> Deconvolution Filter Design for Uncertain Two-Dimensional Markovian Jump Systems With State-Varying Delays

This paper addresses the problem of non-fragile <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> deconvolution filtering for two-dimensional (2-D) Markovian jump systems with state-varying delays and norm-bounded uncertain terms...

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Bibliographic Details
Main Authors: Yakufu Kasimu, Gulijiamali Maimaitiaili
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10851272/
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Summary:This paper addresses the problem of non-fragile <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> deconvolution filtering for two-dimensional (2-D) Markovian jump systems with state-varying delays and norm-bounded uncertain terms. First, 2-D Markovian jump systems are modeled by using Fornasini-Marchesini (FM) model. Based on this system, a 2-D non-fragile <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> deconvolution filter is designed. Second, by utilizing 2-D Lyapunov stability theory, stability criteria are derived to ensure that the filtering error system remains stochastically stable and satisfies the <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance level <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>. Furthermore, sufficient conditions for the mode and delay dependence of the non-fragile <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> deconvolution filter, as well as mode-dependent filter parameters, are achieved by using the linear matrix inequality (LMI) methods. Finally, the feasibility and effectiveness of the proposed non-fragile <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> deconvolution filtering scheme are further demonstrated by an image denoising experiment.
ISSN:2169-3536