Design of optimal digital IIR filters by using a Bandwidth Adaptive Harmony Search algorithm

Ghosh, Sayan; Kundu, Debtosh; Suresh, K.; Das, Swagatam; Abraham, Ajith

doi:10.1109/nabic.2009.5393362

Cited by 9 publications

(1 citation statement)

References 9 publications

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“…These include the Genetic Algorithm (GA) (Holland 1975;Goldberg 1989), Simulated Annealing (SA) (Kirkpatrcik et al 1983), Tabu Search (TS) (Glover 1986(Glover , 1989(Glover , 1990Glover et al 1993), the Immune Algorithm (IA) (Farmer et al 1986;Hunt and Cooke 1996), Particle Swarm Optimization (PSO) (Kennedy and Eberhart 1995), Differential Evolution (DE) (Storn 1997;Kenneth 1999), Harmony Search (HS) (Geem et al 2001), the Clonal Selection Algorithm (CSA) (De Castro and Von Zuben 2002), the Artificial Bee Colony (ABC) (Karaboga 2005) Algorithm, the Bees Algorithm (BA) (Pham et al 2005), the Gravitational Search Algorithm (GSA) (Rashedi et al 2009) and the hybrid or improved version of the above-mentioned algorithms. The majority of the metaheuristic algorithms used can be classified into two groups: evolutionary algorithms, such as genetic algorithms and differential evolution (Ghosh et al 2012;Das and Suganthan 2011) and swarm intelligence based algorithms (Dorigo and Birattari 2007), such as particle swarm optimization, artificial bee colony algorithm, immune algorithm (Timmis et al 2010) and harmony search algorithm (Ghosh et al 2009). The distribution of publications related to evolutionary, swarm intelligence and other algorithms with respect to 2-D digital filter design is presented in Fig.…”

Section: Introductionmentioning

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

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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.

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Section: Introductionmentioning

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

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RETRACTED ARTICLE: Optimization algorithms, an effective tool for the design of digital filters; a review

Ravi¹,

Subramaniam

Roshini³

et al. 2019

J Ambient Intell Human Comput

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A modified imperialist competitive algorithm for digital IIR filter design

Sharifi

Mojallali

2015

2015 the International Symposium on Artificial Intelligence and Signal Processing (AISP)

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Digital infinite impulse response (IIR) filter have become the target of growing interest, because they often provide a much better performance and less computational cost than finite impulse response (FIR) filters. Since the problem of error surface of designing Digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. In this paper, an evolutionary method based on Imperialist Competitive Algorithm (ICA) has been proposed to design Digital IIR filters. By adding a step to the standard ICA algorithm, its performance has been improved in searching solution space and convergence to the global minima. Simulation results show the efficiency of the proposed method to design Digital IIR filter.

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Design of optimal digital IIR filters by using a Bandwidth Adaptive Harmony Search algorithm

Abstract: Abstract

Cited by 9 publications

References 9 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

RETRACTED ARTICLE: Optimization algorithms, an effective tool for the design of digital filters; a review

A modified imperialist competitive algorithm for digital IIR filter design

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