Design of two-dimensional recursive digital filters with specified magnitude and group-delay characteristics using Taguchi-based Immune Algorithm

Abo‐Zahhad, Mohammed; Ahmed, Sabah M.; Al-Ajlouni, Ahmad F.; Sabor, Nabil

doi:10.1504/ijsise.2010.038018

Cited by 12 publications

(9 citation statements)

References 18 publications

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“…The performance of HMAPSO was compared with those of HTGA, MEPSO, DE, G3 with PCX, Quasi-Newton, neural networks and the genetic algorithm. Abo-Zahhad et al (2010) proposed the Taguchi-based immune algorithm to design 2-D recursive filters with specified magnitude and group-delay characteristics. Pham and Koc (2010) solved the constrained optimization problem of 2-D recursive filter design using the bees algorithm (BA).…”

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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“…This paper presents one of the recently multi-objective evolutionary algorithms to solve the above mentioned problem that is called Immune Algorithm (IA). IA is a randomized algorithm inspired by immune functions and principles observed in nature [8] - [9].…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, the energy consumed in moving the sensor (Ernav) is linear with respect to distance it travelled when acceleration is negligible [12] as given by Equation (8). In our centralized algorithm, each sensor will only move once, so its moved distance equals to the distance between the initial position ( X b yJ and final position (Xj; Yj).…”

Section: Coverage Area Objectivementioning

confidence: 99%

C19. Immune node deployment algorithm for mobile wireless sensor networks with limited mobility based on probabilistic sensing model

Abo‐Zahhad

Ahmed

Sabor

et al. 2015

2015 32nd National Radio Science Conference (NRSC)

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Coverage has direct effect on the network performance, thus it considered as the measure of quality of service in WSNs. The deployment strategy of sensor nodes in the sensor field is the most critical factor related to the network coverage. So, in this paper a centralized deployment algorithm based on immune optimization algorithm is proposed to improve the coverage of mobile sensor networks. The proposed algorithm redeploys the random deployed sensor nodes to maximize the coverage area based on a probabilistic sensing model. Moreover, the proposed algorithm limits the moving distance of mobile sensor nodes to reduce the dissipated energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the CSAPO algorithm using MATLAB simulation. Simulation results show that the proposed algorithm outperforms the CSAPO algorithm in terms of the network coverage, mobility cost and convergence speed.

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“…The use of mobile sinks can potentially provide energy-efficient data collection with well-designed networking protocols for WSNs [13]. When using the mobile sink in practice, the sink nodes can be attached to vehicles, animals or people that can move inside the region of interest.…”

Section: Introductionmentioning

confidence: 99%

Mobile Sink Based Low Energy Adaptive Clustering Hierarchy Routing Algorithm in Wireless Sensor Networks

2016

IJAERD

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Design of two-dimensional recursive digital filters with specified magnitude and group-delay characteristics using Taguchi-based Immune Algorithm

Cited by 12 publications

References 18 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

C19. Immune node deployment algorithm for mobile wireless sensor networks with limited mobility based on probabilistic sensing model

Mobile Sink Based Low Energy Adaptive Clustering Hierarchy Routing Algorithm in Wireless Sensor Networks

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