Application of the Algebraic Extension Method to the Construction of Orthogonal Bases for Partial Digital Convolutions

Mathematical tools have been developed that are analogous to the tool that allows one to reduce the description of linear systems in terms of convolution operations to a description in terms of amplitude-frequency characteristics. These tools are intended for use in cases where the system under consideration is described by partial digital convolutions. The basis of the proposed approach is the Fourier–Galois transform using orthogonal bases in corresponding fields. As applied to partial convolutions, the Fourier–Galois transform is decomposed into a set of such transforms, each of which corresponds to operations in a certain Galois field. It is shown that for adequate application of the Fourier–Galois transform to systems described by partial convolutions, it is necessary to ensure the same number of cycles in each of the transforms from the set specified above. To solve this problem, the method of algebraic extensions was used, a special case of which is the transition from real numbers to complex numbers. In this case, the number of cycles varies from p to pn/k, where p is a prime number, n and k are integers, and an arbitrary number divisor of pn can be chosen as k. This allows us to produce partial Fourier–Galois transforms corresponding to different Galois fields, for the same number of cycles. A specific example is presented demonstrating the constructiveness of the proposed approach.

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Publication Details

Journal
Algorithms
Published
2024-11-03
DOI
https://doi.org/10.3390/a17110496
Citations
1
Primary Topic
Digital Filter Design and Implementation
Type
article
Field-Weighted Citation Impact
0.35

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article

Application of the Algebraic Extension Method to the Construction of Orthogonal Bases for Partial Digital Convolutions

Дина Шалтыкова, Akhat Bakirov, Ibragim Esenovich Suleimenov, Aruzhan Kadyrzhan
1 citations
Algorithms
Digital Filter Design and Implementation
0.35
article

Application of the Algebraic Extension Method to the Construction of Orthogonal Bases for Partial Digital Convolutions

Дина Шалтыкова, Akhat Bakirov, Ibragim Esenovich Suleimenov, Aruzhan Kadyrzhan
article en
1 citations

Abstract

Mathematical tools have been developed that are analogous to the tool that allows one to reduce the description of linear systems in terms of convolution operations to a description in terms of amplitude-frequency characteristics. These tools are intended for use in cases where the system under consideration is described by partial digital convolutions. The basis of the proposed approach is the Fourier–Galois transform using orthogonal bases in corresponding fields. As applied to partial convolutions, the Fourier–Galois transform is decomposed into a set of such transforms, each of which corresponds to operations in a certain Galois field. It is shown that for adequate application of the Fourier–Galois transform to systems described by partial convolutions, it is necessary to ensure the same number of cycles in each of the transforms from the set specified above. To solve this problem, the method of algebraic extensions was used, a special case of which is the transition from real numbers to complex numbers. In this case, the number of cycles varies from p to pn/k, where p is a prime number, n and k are integers, and an arbitrary number divisor of pn can be chosen as k. This allows us to produce partial Fourier–Galois transforms corresponding to different Galois fields, for the same number of cycles. A specific example is presented demonstrating the constructiveness of the proposed approach.

AlgorithmsVol. 17(11)
Almaty University of Power Engineering and Telecommunications (KZ), National Academy of Sciences of the Republic of Kazakhstan (KZ)
Uddannelses- og Forskningsministeriet
Openalex Percentile: Top 42%
Digital Filter Design and Implementation
0.35
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Application of the Algebraic Extension Method to the Construction of Orthogonal Bases for Partial Digital Convolutions — Дина Шалтыкова, Akhat Bakirov, et al. · Algorithms (2024) | TGRS Research Map | TGRS