Design of 2-D multiplierless IIR filters using the genetic algorithm

Thamvichai, Ratchaneekorn; Bose, T.; Haupt, Randy L.

doi:10.1109/tcsi.2002.1010045

Cited by 23 publications

(8 citation statements)

References 7 publications

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“…The binary and integer genetic algorithms were employed to optimize the filter design and they were compared with each other for Gaussian filter design. This paper was extended and prepared by Thamvichai et al (2002). Liang et al (2003) proposed a new approach to design a 2-D octagonal symmetric IIR filter with canonical signed digit (CSD) coefficients.…”

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

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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: 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

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“…In the domain of digital circuits, the evolutionary synthesis of digital filters has deserved considerable attention [16,17,[24][25][26][27][28][29][30][31][32][34][35][36]. Digital filters can be classified as Finite Impulse Response (FIR) or Infinite Impulse Response (IIR) according to the length of the impulse response.…”

Section: Introductionmentioning

confidence: 99%

“…In a large amount of works found in the literature [24][25][26][27][28][29][30], the GA is used just as an optimization method to find the multipliers values for a fixed filter topology. On the other hand, only a small number of works [31][32][33][34] addressing the evolutionary synthesis methods deal with the low-sensitivity problem [35,36].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary synthesis of low-sensitivity digital filters using adjacency matrix

Sá

Mesquita

2009

Evol. Intel.

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An evolutionary synthesis method to generate digital filters with low coefficient sensitivity is presented. The method uses a chromosome coding based on the graph adjacency matrix representation. It is shown that the proposed chromosome representation enables to easily verify and avoid the generation of topologically invalid and noncomputable individuals during the evolutionary process. The efficiency of the proposed algorithm is tested in the synthesis of two low-pass digital filters and the results are compared with other examples found in the literature.

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“…In a large number of works found in the literature [5][6][7][8][9][10][11], a Genetic Algorithm (GA) is used just as an optimization method to find the multipliers values for a given fixed filter topology. On the other hand, among the works [12][13][14][15][16][17] addressing the evolutionary synthesis methods only a few deal with the lowsensitivity problem [16][17].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary synthesis of low-sensitivity equalizers using adjacency matrix representation

Sá

Mesquita

2008

Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation

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An evolutionary synthesis method to design low-sensitivity IIR filters with linear phase in the passband is presented. The method uses a chromosome coding scheme based on the graph adjacency matrix. It is shown that the proposed chromosome representation enables to easily verify invalid individuals during the evolutionary process. The efficiency of the proposed algorithm is tested in the synthesis of a fourth-order linear phase elliptic lowpass digital filter.

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Design of 2-D multiplierless IIR filters using the genetic algorithm

Cited by 23 publications

References 7 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

Evolutionary synthesis of low-sensitivity digital filters using adjacency matrix

Evolutionary synthesis of low-sensitivity equalizers using adjacency matrix representation

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