Optimizasyon Tabanlı FIR Süzgeç Tasarımlarında Performans Analizi

Öz

Dijital sinyal işleme sistemleri üzerinde tasarlanarak kullanılan dijital süzgeçlerin sonlu dürtü yanıtlı ve (FIR) ve sonsuz dürtü yanıtlı (IIR) olmak üzere iki çeşidi bulunmaktadır. FIR süzgeçlerin tasarımı esnasında kullanılan iki adet yaklaşım mevcuttur. Bunlardan ilki klasik yöntemler iken diğeri optimizasyon tabanlı yöntemlerdir. Optimizasyon tabanlı yöntemlerde metasezgisel algoritmaların kullanılması özellikle son yıllarda daha performanslı filtre tasarımları gerçekleştirebilmek adına giderek artmaktadır. İdeal süzgece olabildiğince yakın bir süzgeç tasarımı yapabilmek adına bu çalışmada çok amaçlı hata yaklaşımı kullanılarak metasezgisel algoritmalar ile FIR süzgeç tasarımları gerçekleştirilmiş ve tasarlanan bu süzgeçlere ait performans parametreleri analiz edilmiştir. FIR filtre katsayıları Genetik Algoritma, Parçacık Sürü Optimizasyonu Algoritması, Diferansiyel Gelişim Algoritması, Yapay Arı Kolonisi Algoritması, Karadul Örümceği Algoritması, Sincap Arama Algoritması ve Harmoni Arama Algoritmaları kullanılarak optimize edilmiştir. Elde edilen sonuçlar ve literatür çalışmalar karşılaştırıldığında önerilen yaklaşım ile geliştirilen FIR filtrenin performans parametrelerinde önemli iyileşmeler olduğu görülmüştür.

Anahtar Kelimeler

• Metasezgisel Algoritmalar
• FIR Filtre Tasarımı
• Sinyal İşleme
• Optimizasyon.

Performance Analysis in Optimization Based FIR Filter Designs

Abstract

There are two types of digital filters designed and used on digital signal processing systems: finite impulse response (FIR) and infinite impulse response (IIR). There are two approaches used during the design of FIR filters. The first of these is classical methods, while the other is optimization-based methods. The use of metaheuristic algorithms in optimization-based methods has been increasing in recent years, especially in order to realize more performance filter designs. In order to design a filter as close to the ideal as possible, in this study, FIR filter designs were carried out with metaheuristic algorithms using the multi-objective error approach, and the performance parameters of these designed filters were analyzed. FIR filter coefficients were optimized using Genetic Algorithm, Particle Swarm Optimization Algorithm, Artificial Bee Colony Algorithm, Black Widow Algorithm, Squirrel Search Algorithm, and Harmony Search Algorithm. When the obtained results and literature studies were compared, it was seen that there were significant improvements in the performance parameters of the FIR filter obtained with the proposed approach.

Keywords

• Metaheuristic Algorithms
• FIR Filter Design
• Signal Processing
• Optimization.

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