Development of Graphical Analytical Models for Digital Signal Processing System Structures

SUOD, MAHMOUD, Ushkarenka, Alexander, SOLIMAN, Abdel-Hamid, Zeidan, Mahmoud, Awwad, Abdullah and Quteimat, Alaa (2020) Development of Graphical Analytical Models for Digital Signal Processing System Structures. Jordan Journal of Electrical Engineering, 6 (2). p. 140. ISSN 2409-9600

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Abstract or description

This paper proposes an improved method for describing digital filter structures as part of digital signal processing (DSP) systems, characterized by the high information content of its models. The proposed approach is used to perform the synthesis of graphical analytical models of DSP systems as well as their analysis by means of multilevel decomposition. All the system elements are presented in the form of functional structures, and the input counts processing - by the discrete system - is considered as the process of converting arguments by these functional structures. Moreover, graphical analytical models of basic structures of the finite impulse response (FIR) and infinite impulse response (IIR) filters are developed and integrated with an object-oriented programming language to be used in various projects in the form of snap-in modules. Additionally, the method, proposed in this paper is used for synthesising an optimized structure of a digital filter for calculating the mean and current values of the determined periodic signal at the optimal discrete system’s speed and invariance to discretization frequency. The obtained practical results show that the proposed method can be used with great confidence in synthesizing optimized structures of digital filters as well as in the optimization of DSP systems’ structures with the purpose of identifying the mean and RMS voltage values. The latter is an indicator that the proposed method can be applied to various electronic systems.

Item Type:	Article
Faculty:	School of Creative Arts and Engineering > Engineering
Depositing User:	Abdel-Hamid SOLIMAN
Date Deposited:	14 Jul 2020 13:32
Last Modified:	24 Feb 2023 13:59
URI:	https://eprints.staffs.ac.uk/id/eprint/6402

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