EconPapers    
Economics at your fingertips  
 

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

Omar Avalos, Erik Cuevas, Jorge Gálvez, Essam H. Houssein and Kashif Hussain
Additional contact information
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

Mathematics, 2020, vol. 8, issue 8, 1-22

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.

Keywords: filter design; evolutionary computational techniques; signal processing; IIR filters (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/8/8/1226/pdf (application/pdf)
https://www.mdpi.com/2227-7390/8/8/1226/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:8:y:2020:i:8:p:1226-:d:389939

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1226-:d:389939