Volume 42, Issue 5 pp. 1337-1348
RESEARCH ARTICLE

H deconvolution filter for two-dimensional numerical systems using orthogonal moments

Bensalem Boukili

Corresponding Author

Bensalem Boukili

LISAC Laboratory, Faculty of Science Dhar El Mehraz, Sidi Mohamed Ben Abdellah University, Fez-Atlas, Morocco

Correspondence

Bensalem Boukili, Faculty of Science Dhar El Mehraz, B.P. 1796 Fez-Atlas Morocco.

Email: [email protected]

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Mostafa El Mallahi

Mostafa El Mallahi

LIPI Laboratory, High Normal School, Sidi Mohamed Ben Abdellah University, Fez, Morocco

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Abderrahim El-Amrani

Abderrahim El-Amrani

LISAC Laboratory, Faculty of Science Dhar El Mehraz, Sidi Mohamed Ben Abdellah University, Fez-Atlas, Morocco

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Abdelaziz Hmamed

Abdelaziz Hmamed

LISAC Laboratory, Faculty of Science Dhar El Mehraz, Sidi Mohamed Ben Abdellah University, Fez-Atlas, Morocco

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Ismail Boumhidi

Ismail Boumhidi

LISAC Laboratory, Faculty of Science Dhar El Mehraz, Sidi Mohamed Ben Abdellah University, Fez-Atlas, Morocco

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First published: 26 April 2021
Citations: 3

Abstract

In this article, we propose the issue of H deconvolution filtering for two-dimensional (2D) systems described by the Fornasini–Marchesini local state-space model. The main challenge is the design of a deconvolution filter to rebuild the 2D signal so that the filter error system is asymptotically stable and preserves a guaranteed H performance. To overcome this issue, we use some free matrix variables to eliminate coupling between Lyapunov matrix and system matrices to obtain sufficient conditions in linear matrix inequality form to ensure the desired stability and performance of the error systems in the first time. Moreover, we use the orthogonal moments to extract the feature vectors to generate the input system, with the minimum information with and without noise. Simulation examples are provided to show that the new design technology proposed in this article achieves better H performance than the existing design methods. Finally, this work can be very helpful tools for the practitioners in telecommunication, and data scientists to aid them in deconvolution, diagnostic, and transmission.

DATA AVAILABILITY STATEMENT

Data openly available in a public repository that issues datasets with DOIs

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.