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Comparison of Circular Symmetric Low-Pass Digital IIR Filter Design Using Evolutionary Computation Techniques

Author

Listed:
  • Omar Avalos

    (Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución, Guadalajara 1500, Mexico)

  • Erik Cuevas

    (Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución, Guadalajara 1500, Mexico)

  • Jorge Gálvez

    (Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución, Guadalajara 1500, Mexico)

  • Essam H. Houssein

    (Department of Computer Science, Faculty of Computers & Information, Minia University, Minia 61519, Egypt)

  • Kashif Hussain

    (Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China)

Abstract

The design of two-dimensional Infinite Impulse Response (2D-IIR) filters has recently attracted attention in several areas of engineering because of their wide range of applications. Synthesizing a user-defined filter in a 2D-IIR structure can be interpreted as an optimization problem. However, since 2D-IIR filters can easily produce unstable transfer functions, they tend to compose multimodal error surfaces, which are computationally difficult to optimize. On the other hand, Evolutionary Computation (EC) algorithms are well-known global optimization methods with the capacity to explore complex search spaces for a suitable solution. Every EC technique holds distinctive attributes to properly satisfy particular requirements of specific problems. Hence, a particular EC algorithm is not able to solve all problems adequately. To determine the advantages and flaws of EC techniques, their correct evaluation is a critical task in the computational intelligence community. Furthermore, EC algorithms are stochastic processes with random operations. Under such conditions, for obtaining significant conclusions, appropriate statistical methods must be considered. Although several comparisons among EC methods have been reported in the literature, their conclusions are based on a set of synthetic functions, without considering the context of the problem or appropriate statistical treatment. This paper presents a comparative study of various EC techniques currently in use employed for designing 2D-IIR digital filters. The results of several experiments are presented and statistically analyzed.

Suggested Citation

  • Omar Avalos & Erik Cuevas & Jorge Gálvez & Essam H. Houssein & Kashif Hussain, 2020. "Comparison of Circular Symmetric Low-Pass Digital IIR Filter Design Using Evolutionary Computation Techniques," Mathematics, MDPI, vol. 8(8), pages 1-22, July.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1226-:d:389939
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    References listed on IDEAS

    as
    1. Supriya Dhabal & Palaniandavar Venkateswaran, 2014. "Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization," Journal of Optimization, Hindawi, vol. 2014, pages 1-10, September.
    2. Tan, K.C. & Chiam, S.C. & Mamun, A.A. & Goh, C.K., 2009. "Balancing exploration and exploitation with adaptive variation for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 197(2), pages 701-713, September.
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