A new constrained independent component analysis method

被引：108
|
作者：
Huang, De-Shuang [1 ]
Mi, Jian-Xun
机构：
[1] Chinese Acad Sci, Hefei Inst Intelligent Machine, Intelligent Comp Lab, Anhui 230031, Peoples R China
[2] Univ Sci & Technol China, Anhui 230026, Peoples R China
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2007年 / 18卷 / 05期
基金：
中国国家自然科学基金;
关键词：
constrained optimization; electroencephalogram (EEG); ICA with reference (ICA-R); independent component analysis (ICA);
D O I：
10.1109/TNN.2007.895910
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Constrained independent component analysis (cICA) is a general framework to incorporate a priori information from problem into the negentropy contrast function as constrained terms to form an augmented Lagrangian function. In this letter, a new improved algorithm for cICA is presented through the investigation of the inequality constraints, in which different closeness measurements are compared. The utility of our proposed algorithm is demonstrated by the experiments with synthetic data and electroencephalogram (EEG) data.
引用
收藏
页码：1532 / 1535
页数：4
相关论文
共 50 条
  • [41] A New Robust Objective Function Based on Maximum Negentropy Approximation in Independent Component Analysis
    Pingxing Feng
    Liping Li
    Hongbo Zhang
    Wireless Personal Communications, 2014, 79 : 877 - 890
  • [42] Performance comparison of new nonparametric independent component analysis algorithm for different entropic indexes
    Sevim, Yusuf
    Atasoy, Ayten
    TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2012, 20 (03) : 287 - 297
  • [43] A New Robust Objective Function Based on Maximum Negentropy Approximation in Independent Component Analysis
    Feng, Pingxing
    Li, Liping
    Zhang, Hongbo
    WIRELESS PERSONAL COMMUNICATIONS, 2014, 79 (02) : 877 - 890
  • [44] Independent Component Analysis by Entropy Bound Minimization
    Li, Xi-Lin
    Adali, Tuelay
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010, 58 (10) : 5151 - 5164
  • [45] Extraction of Fetal Electrocardiogram by Independent Component Analysis
    Jaros, Rene
    Martinek, Radek
    Barnova, Katerina
    Ladrova, Martina
    2019 INTERNATIONAL SYMPOSIUM ON ADVANCED ELECTRICAL AND COMMUNICATION TECHNOLOGIES (ISAECT), 2019,
  • [46] Independent component analysis using pots models
    Wu, JM
    Chiu, SJ
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 12 (02): : 202 - 211
  • [47] Efficient source adaptivity in independent component analysis
    Vlassis, N
    Motomura, Y
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 12 (03): : 559 - 566
  • [48] Vibration sources identification with independent component analysis
    Ye, Hongxian
    Yang, Shixi
    Yang, Jiangxin
    Ji, Huawei
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 5814 - +
  • [49] A "nonnegative PCA" algorithm for independent component analysis
    Plumbley, MD
    Oja, E
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2004, 15 (01): : 66 - 76
  • [50] Fetal Electrocardiogram Extraction by Independent Component Analysis
    Manorost, Panason
    Theera-Umpon, Nipon
    Auephanwiriyakul, Sansanee
    2017 7TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE), 2017, : 220 - 225
12345