Minimal nonlinear distortion principle for nonlinear independent component analysis

被引:0
作者
Department of Computer Science and Engineering, Chinese University of Hongkong, Hong Kong, Hong Kong [1 ]
机构
来源
J. Mach. Learn. Res. | 2008年 / 2455-2487期
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
[41]   Nonlinear Nonnegative Component Analysis [J].
Zafeiriou, Stefanos ;
Petrou, Maria .
CVPR: 2009 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-4, 2009, :2852-2857
[42]   Symplectic nonlinear component analysis [J].
Parra, LC .
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 8: PROCEEDINGS OF THE 1995 CONFERENCE, 1996, 8 :437-443
[43]   Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity [J].
Pomponi, E ;
Fiori, S ;
Piazza, F .
ICASSP '99: 1999 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS VOLS I-VI, 1999, :1077-1080
[44]   State-space independent component analysis for nonlinear dynamic process monitoring [J].
Odiowei, P. P. ;
Cao, Y. .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2010, 103 (01) :59-65
[45]   Integrating Nonlinear Independent Component Analysis and Neural Network in Stock Price Prediction [J].
Lu, Chi-Jie ;
Chiu, Chih-Chou ;
Yang, Jung-Li .
NEXT-GENERATION APPLIED INTELLIGENCE, PROCEEDINGS, 2009, 5579 :614-+
[46]   A novel recurrent network for independent component analysis of post nonlinear convolutive mixtures [J].
Vigliano, D ;
Parisi, R ;
Uncini, A .
2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS: DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS INDUSTRY TECHNOLOGY TRACKS MACHINE LEARNING FOR SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING SIGNAL PROCESSING FOR EDUCATION, 2004, :553-556
[47]   Fault detection of nonlinear processes using multiway kernel independent component analysis [J].
Zhang, Yingwei ;
Qin, S. Joe .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2007, 46 (23) :7780-7787
[48]   Complex independent component analysis by nonlinear generalized Hebbian learning with Rayleigh nonlinearity [J].
Univ of Ancona, Ancona, Italy .
ICASSP IEEE Int Conf Acoust Speech Signal Process Proc, (1077-1080)
[49]   Speckle removal for ultrasonic NDE images with nonlinear filtering for independent component analysis [J].
Chen, CH ;
Wang, XJ .
INSIGHT, 2003, 45 (11) :740-742
[50]   Independent component analysis by general nonlinear Hebbian-like learning rules [J].
Hyvarinen, A ;
Oja, E .
SIGNAL PROCESSING, 1998, 64 (03) :301-313