Efficient GHA-based hardware architecture for texture classification

Shiow Jyu Lin*, Yi Tsan Hung, 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

摘要

This paper presents a novel hardware architecture based on generalized Hebbian algorithm (GHA) for texture classification. In the architecture, the weight vector updating process is separated into a number of stages for lowering area costs and increasing computational speed. Both the weight vector updating process and principle component computation process can also operate concurrently to further enhance the throughput. The proposed architecture has been embedded in a system-on-programmable-chip (SOPC) platform for physical performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs.

原文英語
主出版物標題Computational Collective Intelligence
主出版物子標題Technologies and Applications - Second International Conference, ICCCI 2010, Proceedings
頁面203-212
頁數10
版本PART 2
DOIs
出版狀態已發佈 - 2010 十二月 6
事件2nd International Conference on Computational Collective Intelligence - Technologies and Applications, ICCCI 2010 - Kaohsiung, 臺灣
持續時間: 2010 十一月 102010 十一月 12

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 2
6422 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他2nd International Conference on Computational Collective Intelligence - Technologies and Applications, ICCCI 2010
國家/地區臺灣
城市Kaohsiung
期間2010/11/102010/11/12

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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