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

研究成果: 書貢獻/報告類型會議論文篇章

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
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/地區中国
城市Beijing
期間2010/06/122010/06/15

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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