Sparse FIR Filter Design using Double Generalized Orthogonal Matching Pursuit (DGOMP)

In this paper, sparse FIR filter was designed using Double Generalized Orthogonal Matching Pursuit (DGOMP) to reduce memory usage and increasing the speed thereby decreasing computational complexity of the algorithm. Mathematical models were formulated and simulations were conducted to validate the...

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Bibliographic Details
Main Authors: Samuel Farayola Kolawole, Farouk Muhammad Isah, Nasiru Ameh Musa, Ashraf Adam Ahmad
Format: Article
Language:English
Published: College of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, Nigeria 2024-08-01
Series:ABUAD Journal of Engineering Research and Development
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Online Access:https://journals.abuad.edu.ng/index.php/ajerd/article/view/355
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Summary:In this paper, sparse FIR filter was designed using Double Generalized Orthogonal Matching Pursuit (DGOMP) to reduce memory usage and increasing the speed thereby decreasing computational complexity of the algorithm. Mathematical models were formulated and simulations were conducted to validate the performance of the proposed method. The performance was compared with BOMP and Conventional FIR filter. The results showed that the DGOMP method achieved higher sparsity and a better approximation of an ideal filter. Additionally, the designed sparse FIR filters using DGOMP showed better performance in terms of time of execution when the signal lengths keep increasing, giving a 10% faster execution time when compared to BOMP. The passband and stopband attenuation, as well as ripple values were better, offering the flexibility of parameter adjustment. The results showed that DGOMP is a promising approach for designing sparse FIR filters.
ISSN:2756-6811
2645-2685