2004Unpublished venueRequires access

Matrix Formulation of Frequency Transformation for 2-D State-Space Digital Filters

Shunsuke Koshita, Masayuki Kawamata

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Abstract

Abstract: This paper proposes matrix formulation of fre-quency transformation for 2-D digital filters in terms of the state-space equations. In order to derive the formulation, we extend Mullis and Roberts ’ matrix formulation of 1-D fre-quency transformation to 2-D case. The proposed formula-tion is very suitable for both analysis and realization of the transformed state-space digital filters since the resultant state-space filter has smaller dimension than that of the filters ob-tained by conventional formulation and consists of simple al-gebraic operations such as matrix addition, multiplication, in-verse and so on. Moreover, our formulation can be easily im-plemented in MATLAB without any complicated algorithm. 1.

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What this paper is about

Abstract: This paper proposes matrix formulation of fre-quency transformation for 2-D digital filters in terms of the state-space equations. In order to derive the formulation, we extend Mullis and Roberts ’ matrix formulation of 1-D fre-quency transformation to 2-D case. The proposed formula-tion is very suitable for both analysis and realization of the transformed state-space digital filters since the resultant state-space filter has smaller dimension than that of the filters ob-tained by conventional formulation and consists of simple al-gebraic operations such as matrix addition, multiplication, in-verse and so on. Moreover, our formulation can be easily im-plemented in MATLAB without any complicated algorithm. 1.

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Available abstract

Abstract: This paper proposes matrix formulation of fre-quency transformation for 2-D digital filters in terms of the state-space equations. In order to derive the formulation, we extend Mullis and Roberts ’ matrix formulation of 1-D fre-quency transformation to 2-D case. The proposed formula-tion is very suitable for both analysis and realization of the transformed state-space digital filters since the resultant state-space filter has smaller dimension than that of the filters ob-tained by conventional formulation and consists of simple al-gebraic operations such as matrix addition, multiplication, in-verse and so on. Moreover, our formulation can be easily im-plemented in MATLAB without any complicated algorithm. 1.

Key concepts: Transformation (genetics), State space, Matrix (chemical analysis), State (computer science), Computer science, Transformation matrix, Mathematics, Algorithm

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