Digital filters design educational software based on immune, genetic and quasi-Newton line search algorithms

Mohammed Abo-Zahhad, Sabah M. Ahamed, Ahmad F. Al-Ajlouni and Nabil Sabor

International Journal of Innovation and Learning, 2011, vol. 9, issue 1, 35-62

Abstract: This paper presents educational software developed for designing FIR and IIR digital filters using two evolutionary algorithms (EAs); namely immune algorithms (IAs) and genetic algorithms (GAs), together with quasi-Newton line search algorithm (QNLS). This software provides the user the ability to design one- and two-dimensional; low-pass, high-pass, band-pass and band-stop digital filters with arbitrary magnitude and group delay specifications. The software is evaluated by making the assessment quizzes for electrical engineering students and instructors. Students' responses are very positive. A number of recommendations are made in this work based on instructor observation and students' evaluations.

Keywords: evolutionary algorithms; immune algorithms; genetic algorithms; quasi-Newton line search algorithms; blended teaching; blended learning; educational software; filter design; infinite impulse response; IIR; finite impulse response; FIR; one-dimensional digital filters; two-dimensional digital filters; low-pass digital filters; high-pass digital filters; band-pass digital filters; band-stop digital filters; arbitrary magnitude; group delay; software evaluation; assessment quizzes; electrical engineering education; instructor observation; innovation. (search for similar items in EconPapers)
Date: 2011
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