Improved LMI-based criterion for global asymptotic stability of 2-D state-space digital filters described by Roesser model using twoʼs complement arithmetic

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Abstract

An LMI-based criterion for the global asymptotic stability of 2-D state-space digital filters described by the Roesser model employing twoʼs complement overflow arithmetic is presented. Under a certain assumption, the criterion turns out to be an improvement over a criterion due to El-Agizi and Fahmy pertaining to twoʼs complement arithmetic and has a form similar to a criterion due to Xiao and Hill pertaining to saturation arithmetic. Examples show the effectiveness of the new criterion.

Section snippets

Vimal Singh was born in Mirzapur, India, on May 3, 1946. He received the B.Sc. Eng. and M.Sc. Eng. degrees from Banaras Hindu University (BHU), Varanasi, India, in 1969 and 1971, respectively, and the Ph.D. degree from the University of Allahabad, Allahabad, India, in 1976.

He was a Lecturer with BHU from 1971 to 1972. He joined Motilal Nehru National Institute of Technology (MNNIT), Allahabad, as Lecturer in 1972, where he became reader in 1978 and Professor in 1987. He served as Head of

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    Vimal Singh was born in Mirzapur, India, on May 3, 1946. He received the B.Sc. Eng. and M.Sc. Eng. degrees from Banaras Hindu University (BHU), Varanasi, India, in 1969 and 1971, respectively, and the Ph.D. degree from the University of Allahabad, Allahabad, India, in 1976.

    He was a Lecturer with BHU from 1971 to 1972. He joined Motilal Nehru National Institute of Technology (MNNIT), Allahabad, as Lecturer in 1972, where he became reader in 1978 and Professor in 1987. He served as Head of Electronics Engineering Department at MNNIT from 1996 to 1999. He was a visiting Lecturer at University of Mosul, Mosul, Iraq, and University of Basra, Basra, Iraq, from 1978 to 1979 and from 1981 to 1982, respectively. Since 2002 he is a Professor at Atilim University, Ankara, Turkey. His research interests are in finite wordlength effects in digital signal processing, analog circuits, nonlinear systems, multidimensional systems, stability of neural networks, and model reduction.

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