The differential evolution (DE) algorithm is a new heuristic approach with three main advantages: it finds the true global minimum of a multimodal search space regardless of the initial parameter values, it has fast convergence, and it uses only a few control parameters. The DE algorithm, which has been proposed particularly for numeric optimization problems, is a population-based algorithm like the genetic algorithms and uses similar operators: crossover, mutation, and selection. In this work, the DE algorithm has been applied to the design of digital finite impulse response filters, and its performance has been compared to that of the genetic algorithm and least squares method.

Abstract. Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum of a multi modal search space regardless of the initial parameter values, fast convergence, and using a few control parameters. DE algorithm which has been proposed particulary for numeric optimization problems is a population based algorithm like genetic algorithms using the similar operators; crossover, mutation and selection. In this work, DE algorithm has been applied to the design of digital Finite Impulse Response filters and compared its performance to that of genetic algorithm.

ÖzetçeHerhangi bir sayısal işaret işleme (DSP) algoritması veya işlemcisi, sayısal süzgeç olarak tanımlanabilir. Sonsuz darbe cevaplı (IIR) süzgeçlerin temel avantajı, aynı dereceden sonlu darbe cevaplı (FIR) süzgeçlere göre çok daha iyi performanslara sahip olmalarıdır. Bununla birlikte, bu süzgeçlerin hata yüzeyleri çok modlu bir yapıya sahip olabilmektedir. Diferansiyel gelişim (DE) algoritması üç temel avantaja sahip yeni bir sezgisel yaklaşımdır. Bu avantajlar : çok modlu bir araştırma uzayındaki evrensel minimayı bulabilme kabiliyetleri, yerel yakınsama hızlarının çok yüksek olması ve az sayıda kontrol parametresi kullanmasıdır. Bu çalışmada, DE algoritması IIR süzgeç tasarımına uygulanmış ve genetik algoritma ile performansları mukayese edilmiştir. AbstractAny digital signal processing algorithm or processor can be reasonably described as a digital filter. The main advantage of an infinite impulse response filter is that it can provide a much better performance than the finite impulse response filter having the same number of coefficients. However, they might have a multi-modal error surface. Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum of a multi modal search space, fast convergence, and using a few control parameters. In this work, DE algorithm has been applied to the design of digital IIR filters and compared its performance to that of genetic algorithm.

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