Using wavelet transform and partial distance search to implement kNN classifier on FPGA with multiple modules

Hui Ya Li, Yao Jung Yeh, Wen Jyi Hwang*

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

2 引文 斯高帕斯(Scopus)

摘要

This paper presents a novel algorithm of using wavelet transform and partial distance search (PDS) to realize the kNN classifier on field programmable gate array (FPGA) with multiple modules. The algorithm identifies first k closest vectors in the design set of a kNN classifier for each input vector by performing the PDS in the wavelet domain, and allows concurrent classification of different input vectors for further computation acceleration by employing multiple-module PDS. For the effective reduction of the area complexity and computation latency, we proposed a novel PDS algorithm well-suited for hardware implementation and also employ subspace search, bitplane reduction and multiplecoefficient accumulation techniques. The proposed realization has been embedded in a softcore CPU for physical performance measurements. Experimental results show that the proposed realization not only provides a cost-effective solution to the FPGA implementation of kNN classification systems, but also meets both high throughput and low area cost.

原文英語
主出版物標題Image Analysis and Recognition - 4th International Conference, ICIAR 2007, Proceedings
發行者Springer Verlag
頁面1105-1116
頁數12
ISBN(列印)9783540742586
DOIs
出版狀態已發佈 - 2007
事件4th International Conference on Image Analysis and Recognition, ICIAR 2007 - Montreal, 加拿大
持續時間: 2007 八月 222007 八月 24

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4633 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他4th International Conference on Image Analysis and Recognition, ICIAR 2007
國家/地區加拿大
城市Montreal
期間2007/08/222007/08/24

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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