Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 程伯中教授 (电子工程学系) |
全文
| 数位物件识别号 (DOI) http://dx.doi.org/10.1109/78.942640 |
引用次数
Web of Sciencehttp://aims.cuhk.edu.hk/converis/portal/Publication/31WOS source URL
其它资讯
摘要An information criterion for adaptively estimating multiple minor eigencomponents of a covariance matrix is proposed. It is proved that the proposed criterion has a unique global minimum at the minor subspace and that all other equilibrium points are saddle points. Based on the gradient search approach of the proposed information criterion, an adaptive algorithm called adaptive minor component extraction (AMEX) is developed. The proposed algorithm automatically performs the multiple minor component extraction in parallel without the inflation procedure. Similar to the adaptive lattice filter structure, the AMEX algorithm also has the flexibility wherein increasing the number of the desired minor component does not affect the previously extracted minor components. The AMEX algorithm has a highly modular structure and the various modules operate completely in parallel without any delay. Simulation results are given to demonstrate the effectiveness of the AMEX algorithm for both the minor component analysis (MCA) and the minor subspace analysis (MSA).
着者Ouyang S, Bao Z, Liao GS, Ching PC
期刊名称IEEE Transactions on Signal Processing
出版年份2001
月份9
日期1
卷号49
期次9
出版社IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
页次2127 - 2137
国际标準期刊号1053-587X
电子国际标準期刊号1941-0476
语言英式英语
关键词adaptive algorithm; information criterion; minor component extraction; neural networks; parallel implementation; stability analysis
Web of Science 学科类别Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC
