Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Wu, Lianghong; Wang, Yaonan; Yuan, Xiaofang

doi:10.2991/ijcis.2011.4.4.20

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…The mutation operator based on "best" takes the parameter vector with best fitness in the contemporary population as a base vector, which has good local exploitation ability and fast convergence rate, but easy to fall into local optimal solution, causing search stagnation and premature convergence. Considering the advantages of two mutation operators, a new self-adaptive mutation operator is proposed based on Wu et al 21 The mutation operator is shown in equation ( 17)…”

Section: Self-adaptive Mutation Differential Evolution Constrained Optimization Algorithmmentioning

confidence: 99%

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Optimum manipulator path generation based on improved differential evolution constrained optimization algorithm

Fan

Xie

Zhou

2019

International Journal of Advanced Robotic Systems

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A new improved differential evolution constrained optimization algorithm is proposed to determine the optimum path generation of a rock-drilling manipulator with nine degrees of freedom. This algorithm is developed to minimize the total joint displacement without compromising the pose accuracy of the end-effector. Considering the rule for optimal operation time and smooth joint motion, total joint displacement and minimization of the end-effector pose error are respectively taken as the optimization objective and constraints. In the proposed algorithm, the inverse kinematics solution is computed by self-adaptive mutation differential evolution constrained optimization (SAMDECO) algorithm. Unlike conventional differential evolution (DE) algorithms, in the process of selection operation, the proposed algorithm takes full advantages of the information of excellent infeasible solutions in the contemporary population and scales the contribution of position constraint and orientation constraint. Consequently, the search process is guided to approach the optimal solution from both feasible and infeasible regions, which tremendously improves convergence accuracy and convergence rate. Some contrastive experiments are conducted with the basic self-adaptive mutation differential evoluton (SAMDE) algorithm. The results indicate that the proposed algorithm outperforms the basic SAMDE algorithm in terms of compliance of joints, which raises operation efficiency and plays an important role in engineering services value.

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Section: Self-adaptive Mutation Differential Evolution Constrained Optimization Algorithmmentioning

confidence: 99%

“…where p 1 and p 2 represent weighting factors of position constraint and orientation constraint, respectively, to normalize the corresponding values in equation (21). We propose to choose p 1 and p 2 suggested in Tabandeh et al 8 as shown in equations ( 22) and ( 23)…”

Section: Is Outlined Asmentioning

confidence: 99%

Optimum manipulator path generation based on improved differential evolution constrained optimization algorithm

Fan

Xie

Zhou

2019

International Journal of Advanced Robotic Systems

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“…Video signal processing contains 3-D digital signals and their applications (Bovik 2005). Multidimensional signal processing deals with two, three and more dimensional digital signals (Dudgeon and Mersereau 1983;Woods 2006).…”

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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Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Cited by 2 publications

References 12 publications

Optimum manipulator path generation based on improved differential evolution constrained optimization algorithm

Optimum manipulator path generation based on improved differential evolution constrained optimization algorithm

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

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