Efficient GHA-based hardware architecture for texture classification

Shiow-Jyu Lin*, Yi Tsan Hung, Wen Jyi Hwang

*Corresponding author for this work

研究成果: Conference contribution同行評審

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English
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Published - 6 十二月 2010
事件2nd International Conference on Computational Collective Intelligence - Technologies and Applications, ICCCI 2010 - Kaohsiung, Taiwan
持續時間: 10 十一月 201012 十一月 2010

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

Conference

Conference2nd International Conference on Computational Collective Intelligence - Technologies and Applications, ICCCI 2010
國家Taiwan
城市Kaohsiung
期間10/11/1012/11/10

指紋 深入研究「Efficient GHA-based hardware architecture for texture classification」主題。共同形成了獨特的指紋。

引用此