Fast principal component analysis based on hardware architecture of generalized hebbian algorithm

Shiow Jyu Lin; Yi Tsan Hung; Wen Jyi Hwang

doi:10.1007/978-3-642-16493-4_51

Fast principal component analysis based on hardware architecture of generalized hebbian algorithm

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

^*此作品的通信作者

資訊工程學系

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 hardware architecture for fast principle component analysis (PCA). The architecture is developed based on generalized Hebbian algorithm (GHA). In the architecture, the updating of different synaptic weight vectors are divided into a number of stages. The results of precedent stages are used for the computation of subsequent stages for expediting training speed and lowering the area cost. 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 effective alternative for fast PCA in attaining both high performance and low computation time.

原文	英語
主出版物標題	Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings
頁面	505-515
頁數	11
版本	M4D
DOIs	https://doi.org/10.1007/978-3-642-16493-4_51
出版狀態	已發佈 - 2010
事件	5th International Symposium on Advances in Computation and Intelligence, ISICA 2010 - Wuhan, 中国持續時間: 2010 10月 22 → 2010 10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)
號碼	M4D
卷	6382 LNCS
ISSN（列印）	0302-9743
ISSN（電子）	1611-3349

其他

其他	5th International Symposium on Advances in Computation and Intelligence, ISICA 2010
國家/地區	中国
城市	Wuhan
期間	2010/10/22 → 2010/10/24

ASJC Scopus subject areas

理論電腦科學
一般電腦科學

存取文件

10.1007/978-3-642-16493-4_51

其它文件與鏈接

引用此

Lin, S. J., Hung, Y. T., & Hwang, W. J. (2010). Fast principal component analysis based on hardware architecture of generalized hebbian algorithm. 於 Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings (M4D 編輯, 頁 505-515). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 6382 LNCS, 編號 M4D). https://doi.org/10.1007/978-3-642-16493-4_51

Fast principal component analysis based on hardware architecture of generalized hebbian algorithm. / Lin, Shiow Jyu; Hung, Yi Tsan; Hwang, Wen Jyi.
Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings. M4D. 編輯 2010. p. 505-515 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 6382 LNCS, 編號 M4D).

研究成果: 書貢獻/報告類型 › 會議論文篇章

Lin, SJ, Hung, YT & Hwang, WJ 2010, Fast principal component analysis based on hardware architecture of generalized hebbian algorithm. 於 Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings. M4D edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 編號 M4D, 卷 6382 LNCS, 頁 505-515, 5th International Symposium on Advances in Computation and Intelligence, ISICA 2010, Wuhan, 中国, 2010/10/22. https://doi.org/10.1007/978-3-642-16493-4_51

Lin SJ, Hung YT, Hwang WJ. Fast principal component analysis based on hardware architecture of generalized hebbian algorithm. 於 Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings. M4D 編輯 2010. p. 505-515. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); M4D). doi: 10.1007/978-3-642-16493-4_51

Lin, Shiow Jyu ; Hung, Yi Tsan ; Hwang, Wen Jyi. / Fast principal component analysis based on hardware architecture of generalized hebbian algorithm. Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings. M4D. 編輯 2010. 頁 505-515 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); M4D).

@inproceedings{6f91b1993a9f4b70aa9700d553c211ce,

title = "Fast principal component analysis based on hardware architecture of generalized hebbian algorithm",

abstract = "This paper presents a novel hardware architecture for fast principle component analysis (PCA). The architecture is developed based on generalized Hebbian algorithm (GHA). In the architecture, the updating of different synaptic weight vectors are divided into a number of stages. The results of precedent stages are used for the computation of subsequent stages for expediting training speed and lowering the area cost. 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 effective alternative for fast PCA in attaining both high performance and low computation time.",

author = "Lin, {Shiow Jyu} and Hung, {Yi Tsan} and Hwang, {Wen Jyi}",

year = "2010",

doi = "10.1007/978-3-642-16493-4_51",

language = "English",

isbn = "3642164927",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "M4D",

pages = "505--515",

booktitle = "Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings",

edition = "M4D",

note = "5th International Symposium on Advances in Computation and Intelligence, ISICA 2010 ; Conference date: 22-10-2010 Through 24-10-2010",

}

TY - GEN

T1 - Fast principal component analysis based on hardware architecture of generalized hebbian algorithm

AU - Lin, Shiow Jyu

AU - Hung, Yi Tsan

AU - Hwang, Wen Jyi

PY - 2010

Y1 - 2010

N2 - This paper presents a novel hardware architecture for fast principle component analysis (PCA). The architecture is developed based on generalized Hebbian algorithm (GHA). In the architecture, the updating of different synaptic weight vectors are divided into a number of stages. The results of precedent stages are used for the computation of subsequent stages for expediting training speed and lowering the area cost. 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 effective alternative for fast PCA in attaining both high performance and low computation time.

AB - This paper presents a novel hardware architecture for fast principle component analysis (PCA). The architecture is developed based on generalized Hebbian algorithm (GHA). In the architecture, the updating of different synaptic weight vectors are divided into a number of stages. The results of precedent stages are used for the computation of subsequent stages for expediting training speed and lowering the area cost. 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 effective alternative for fast PCA in attaining both high performance and low computation time.

UR - http://www.scopus.com/inward/record.url?scp=78649518967&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78649518967&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-16493-4_51

DO - 10.1007/978-3-642-16493-4_51

M3 - Conference contribution

AN - SCOPUS:78649518967

SN - 3642164927

SN - 9783642164927

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 505

EP - 515

BT - Advances in Computation and Intelligence - 5th International Symposium, ISICA 2010, Proceedings

T2 - 5th International Symposium on Advances in Computation and Intelligence, ISICA 2010

Y2 - 22 October 2010 through 24 October 2010

ER -

Fast principal component analysis based on hardware architecture of generalized hebbian algorithm

摘要

出版系列

其他

ASJC Scopus subject areas

存取文件

其它文件與鏈接

指紋

引用此