A Clustering-Based Approach for Designing Low Complexity FIR Filters

Nassralla, Mohammad H.; Akl, Naeem; Dawy, Zaher

doi:10.1109/lsp.2021.3050916

Cited by 7 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among the FIR filter design techniques, the most superior designs are achieved through optimization methods, and ongoing research is dedicated to advancing this methodology [2][3][4][5]. Nonetheless, optimization-driven approaches demand substantial computational resources, rendering them impractical for real-time applications.…”

Section: Introductionmentioning

confidence: 99%

New Hybrid Windows Based on Cosh Window and Their Performance Analysis in Fir Digital Filter Design

Coşkun,

Avcı

2024

KONJES

View full text Add to dashboard Cite

FIR filters find extensive use in various applications such as audio processing, image processing, communications, and control systems. Improving the design methods for FIR filters can lead to better performance in these critical areas. This study introduces novel hybrid window functions, or abbreviated as "windows", to design FIR filters. These newly proposed windows are created by hybridizing two-parameter Cosh window with various one-parameter windows in the existing literature. The performance of these hybrid windows in designing filters is thoroughly examined. Simulation results, conducted in Matlab programming environment, demonstrate that nine proposed hybrid windows exhibit better filter characteristics compared to the Cosh window. Furthermore, for the filter lengths of N = 51 and 101, the filters designed using the proposed windows are compared with those designed using two-parameter windows from the literature, focusing on achieving minimum stopband attenuation for a fixed transition width. The findings reveal that the Cosh-Hamming and Cosh-Von Hann hybrid windows outperform other well-known windows in producing filtering.

show abstract

Section: Introductionmentioning

confidence: 99%