计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220700026-5.doi: 10.11896/jsjkx.220700026

• 人工智能 • 上一篇    下一篇

多策略离散人工蜂群算法设计FIR低通数字滤波器

邵鹏   

  1. 江西农业大学计算机与信息工程学院 南昌 330045
  • 出版日期:2023-06-10 发布日期:2023-06-12
  • 通讯作者: 邵鹏(sp198310@163.com)
  • 基金资助:
    江西省教育厅科技项目(GJJ200424)

FIR Low Pass Digital Filter Based on Multi-strategy Discrete Artificial Bee Colony Algorithm

SHAO Peng   

  1. School of Computer and Information Engineering,Jiangxi Agricultural University,Nanchang 330045,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:SHAO Peng,born in 1983,Ph.D.His main research interests include artificial intelligence,large-scale optimization,image processing and related real world applications.
  • Supported by:
    Science and Technology Plan Projects of Jiangxi Provincial Education Department(GJJ200424).

摘要: 针对人工蜂群(Artificial Bee Colony,ABC)算法在解决复杂问题表现出来精度不高以及收敛速度较慢的不足,提出了一种融合折射学习和Lévy飞行的多策略离散人工蜂群算法(Discrete Artificial Bee Colony Fusing Refraction Learning and Lévy flight,DABC-RL),用于设计有限长脉冲响应(Finite Impulse Response,FIR)低通数字滤波器,以期进一步提高其滤波性能。在DABC-RL算法中,一方面,Lévy飞行策略用于增强ABC算法的局部搜索能力,折射学习用于增强ABC算法的全局搜索能力;另一方面,通过设计合适的离散编码方案对DABC-RL算法中的候选解进行离散化,使其适合于设计FIR低通数字滤波器。为了测试所提的DABC-RL算法设计的FIR低通数字滤波器的性能,选取由ABC算法、基于折射学习的refrPSO算法所设计的FIR低通数字滤波器作为对比算法。实验结果表明,相比其他算法,DABC-RL算法所设计的FIR低通数字滤波器的性能最好,且获得了最快的收敛精度和收敛速度。

关键词: 多策略离散人工蜂群算法, 折射学习, Lévy 飞行, FIR低通数字滤波器

Abstract: Aiming at the shortcomings of artificial bee colony(ABC) algorithm in solving complex problems,such as lower accuracy and slower convergence speed,a discrete artificial bee colony fusing the refraction learning and Lévy flight(DABC-RL) algorithm is proposed to design finite impulse response(FIR) low-pass digital filter,so as to further improve its filtering performance.In the DABC-RL algorithm,on the one hand,Lévy flight strategy is used to enhance its local search ability,and refraction learning is employed to enhance its global search ability.On the other hand,the candidate solution in the DABC-RL algorithm is discretized by designing an appropriate discrete coding scheme,which makes it suitable for designing FIR low pass digital filter.In order to test the performance of the FIR low-pass digital filter designed by the proposed DABC-RL algorithm,the FIR low-pass digital filters designed by ABC algorithm and the refrPSO algorithm based on the refraction learning is selected as two comparative algorithms.Experimental results and analysis show that compared with other algorithms,the FIR low-pass digital filter designed by DABC-RL algorithm has the best performance,and obtains the fastest convergence accuracy and convergence speed.

Key words: Multi-strategy discrete artificial bee colony algorithm, Refraction learning, Lévy flight, FIR low pass digital filter

中图分类号: 

  • TP301
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