Fast parallel memetic algorithm for vector quantization based for reconfigurable hardware and softcore processor

研究成果: 書貢獻/報告類型會議貢獻

摘要

A novel parallel memetic algorithm (MA) architecture for the design of vector quantizers is presented in this paper. The architecture contains a number of modules operating memetic optimization concurrently. Each module uses steady-state genetic algorithm (GA) for global search, and K-means algorithm for local refinement. A shift register based circuit for accelerating mutation and crossover operations for steady state GA operations is adopted in the design. A pipeline architecture for the hardware implementation of K-means algorithm is also used. The proposed architecture is embedded in a softcore CPU, and implemented on a field programmable logic array (FPGA) device for physical performance measurement.

原文英語
主出版物標題Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings
頁面479-488
頁數10
版本PART 1
DOIs
出版狀態已發佈 - 2010 七月 21
事件1st International Conference on Advances in Swarm Intelligence, ICSI 2010 - Beijing, 中国
持續時間: 2010 六月 122010 六月 15

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 1
6145 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他1st International Conference on Advances in Swarm Intelligence, ICSI 2010
國家中国
城市Beijing
期間10/6/1210/6/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • 引用此

    Yu, T. Y., Hwang, W. J., & Chiang, T. C. (2010). Fast parallel memetic algorithm for vector quantization based for reconfigurable hardware and softcore processor. 於 Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings (PART 1 編輯, 頁 479-488). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 6145 LNCS, 編號 PART 1). https://doi.org/10.1007/978-3-642-13495-1_59