Optimization of IIR Digital Filters Using Differential Evolution: A Comparative Analysis of FDDE and AMECoDEs Algorithms

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Εκδόθηκε σε:International Journal of Advanced Computer Science and Applications vol. 16, no. 3 (2025)
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024 7 |a 10.14569/IJACSA.2025.0160317  |2 doi 
035 |a 3192357913 
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100 1 |a PDF 
245 1 |a Optimization of IIR Digital Filters Using Differential Evolution: A Comparative Analysis of FDDE and AMECoDEs Algorithms 
260 |b Science and Information (SAI) Organization Limited  |c 2025 
513 |a Journal Article 
520 3 |a Infinite impulse response (IIR) digital filters are fundamental components in various digital signal processing applications, particularly those requiring optimized use of computational resources, such as memory and processing power. This study presents the design of classical IIR filters, including low-pass, high-pass, band-pass, and band-stop configurations, as well as multiple-passband filters featuring dual and triple passbands. Two differential evolution algorithms are utilized: FDDE (Differential Evolution Algorithm with Fitness and Diversity Ranking-Based Mutation Operator) and AMECoDEs (Adaptive Multiple-Elites-Guided Composite Differential Evolution Algorithm with a Shift Mechanism). To date, no study has investigated the application of the FDDE algorithm to IIR digital filter design, whereas the AMECoDEs algorithm has seen limited application in this context. Consequently, this work investigates the design of IIR filters using these algorithms and assesses their performance based on the mean squared error (MSE). Comparative analysis reveals that, for classical filters, the FDDE algorithm yields a slightly lower MSE in the magnitude response compared to the AMECoDEs algorithm. Conversely, for multiple-passband filters, the AMECoDEs algorithm outperforms FDDE by achieving a lower MSE. In the proposed model, IIR filters are implemented using a cascade structure of second-order sections (SOS), with their fitness function evaluated based on the MSE, computed using a constant weight function within each frequency band. Additionally, the magnitude response characteristics of the designed filters are compared with those of classical and dual-passband filters designed with the AMECoDEs algorithm in recent studies. The results indicate that the filters designed in this study show significant improvements across most evaluated metrics, particularly in terms of improved stopband attenuation. One of the key contributions of this work is the novel application of differential evolution algorithms to the design of triple-passband IIR filters, demonstrating their effectiveness through successful validation on a development board. 
653 |a Evolutionary computation 
653 |a Digital signal processing 
653 |a Operators (mathematics) 
653 |a Digital filters 
653 |a Frequencies 
653 |a Filter design (mathematics) 
653 |a Error analysis 
653 |a Weighting functions 
653 |a Impulse response 
653 |a Low pass filters 
653 |a Evolutionary algorithms 
653 |a IIR filters 
653 |a Computer science 
653 |a Optimization techniques 
653 |a Signal processing 
653 |a Design specifications 
653 |a Linear programming 
653 |a Algorithms 
653 |a Comparative analysis 
773 0 |t International Journal of Advanced Computer Science and Applications  |g vol. 16, no. 3 (2025) 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3192357913/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3192357913/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch