Mixed constrained image filter design using particle swarm optimization

Zhiguo Bao, Takahiro Watanabe

研究成果: Article査読

4 被引用数 (Scopus)

抄録

This article describes an evolutionary image filter design for noise reduction using particle swarm optimization (PSO), where mixed constraints on the circuit complexity, power, and signal delay are optimized. First, the evaluated values of correctness, complexity, power, and signal delay are introduced to the fitness function. Then PSO autonomously synthesizes a filter. To verify the validity of our method, an image filter for noise reduction was synthesized. The performance of the resultant filter by PSO was similar to that of a genetic algorithm (GA), but the running time of PSO is 10% shorter than that of GA.

本文言語English
ページ(範囲)363-368
ページ数6
ジャーナルArtificial Life and Robotics
15
3
DOI
出版ステータスPublished - 2010 1 1

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)
  • 人工知能

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