Design of Two-Dimensional IIR Filters Using an Improved DE Algorithm

Das, Swagatam; Dey, Debangshu

doi:10.1007/11590316_56

Cited by 2 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The result of the PSO-DV algorithm was compared with that of the genetic algorithm. Das and Dey (2005) improved the differential evolution (DE-RANDSF) algorithm to realize a 2-D IIR filter. The performance of the improved DE was compared with those of the genetic algorithm and neural networks.…”

Section: Design Techniques Of 2-d Iir Digital Filtersmentioning

confidence: 99%

The design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms: a review of the literature

Koçkanat

Karaboğa

2015

Artif Intell Rev

View full text Add to dashboard Cite

Recently, the design of the two-dimensional digital filter has become a subject of interest in the field of two-dimensional signal processing. The two-dimensional digital filter has been applied in many important areas such as image processing, television systems and seismic signal processing. In digital filter design, there are several indispensable aims such as stability, reduced computational complexity and computational time. Thus, researchers and practitioners have investigated various advanced methods based on metaheuristic optimization algorithms for the design of the two-dimensional digital filter. Metaheuristic optimization algorithms have been applied to solve different complicated problems in various fields and they have also been successfully used in digital filter design. This paper presents a review of the design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms such as the genetic algorithm, differential evolution and particle swarm optimization. By comparing the proposed design approaches based on metaheuristic optimization algorithms, it is observed that the genetic algorithm is the most preferred algorithm and emerging novel algorithms using metaheuristic optimization algorithms have better performance in terms of computational complexity and computational time. It is hoped that this review will be helpful for researchers and practitioners studying the design of twodimensional digital filters.

show abstract

Section: Design Techniques Of 2-d Iir Digital Filtersmentioning

confidence: 99%

The design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms: a review of the literature

Koçkanat

Karaboğa

2015

Artif Intell Rev

View full text Add to dashboard Cite

show abstract

“…All selected techniques have been set with a population of 25 elements, while the stop criteria is configured to 3000 iterations. In contrast with most of the related works that usually employ less than 500 iterations [16,43,45], in this manuscript, the maximum iterations number is set as 3000 in order to perform a convergence analysis, which is described in Section 4.2. In this work, the produced filters have not been implemented in the hardware of fixed arithmetic.…”

mentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

Design of Two-Dimensional IIR Filters Using an Improved DE Algorithm

Cited by 2 publications

References 5 publications

The design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms: a review of the literature

The design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms: a review of the literature

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

Contact Info

Product

Resources

About