Constrained Independent Component Analysis Techniques

被引：0
作者：
Zhao, Yongjian [1 ]
Jiang, Haining [1 ]
Kong, Xiaoming [1 ]
Qu, Meixia [1 ]
机构：
[1] Shandong Univ Weihai, Inst Informat Engn, Weihai, Peoples R China
来源：
2014 IEEE WORKSHOP ON ELECTRONICS, COMPUTER AND APPLICATIONS | 2014年
关键词：
component; Matrix; Analysis; Source; Optimization; ICA;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Independent component analysis (ICA) is a promising statistical signal processing technique. To overcome the inherent drawbacks encountered in the conventional ICA method, a general framework of constrained ICA is introduced. The prior knowledge of reference is incorporated into a negentropy based objective function so as to construct a constrained ICA problem. Subsequently, a flexible constrained ICA algorithm is derived for extraction of one or a few desired source signals. The utility of the proposed algorithm is demonstrated by computer simulations on real ECG data.
引用
收藏
页码：419 / 422
页数：4
相关论文
共 50 条
  • [41] Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis
    DeRamus, Thomas
    Iraji, Armin
    Fu, Zening
    Silva, Rogers
    Stephen, Julia
    Wilson, Tony W.
    Wang, Yu Ping
    Du, Yuhui
    Liu, Jingyu
    Calhoun, Vince
    2021 IEEE 21ST INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (IEEE BIBE 2021), 2021,
  • [42] Analysis of ST/QT Dynamics Using Independent Component Analysis
    Prasad, S. Thulasi
    Varadarajan, S.
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING SYSTEMS, ICSCS 2015, VOL 1, 2016, 397 : 929 - 937
  • [43] Removal Artifacts from EEG Signal Using Independent Component Analysis and Principal Component Analysis
    Turnip, Arjon
    Junaidi, Edy
    2014 2ND INTERNATIONAL CONFERENCE ON TECHNOLOGY, INFORMATICS, MANAGEMENT, ENGINEERING, AND ENVIRONMENT (TIME-E 2014), 2014, : 296 - 302
  • [44] The Comparison of Iris Recognition Using Principal Component Analysis, Independent Component Analysis and Gabor Wavelets
    Shi, Jin-Xin
    Gu, Xiao-Feng
    PROCEEDINGS 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, (ICCSIT 2010), VOL 1, 2010, : 61 - 64
  • [45] Flexible Constrained Techniques for Source Separation
    Zhao, Yong-jian
    2016 INTERNATIONAL CONFERENCE ON APPLIED MECHANICS, ELECTRONICS AND MECHATRONICS ENGINEERING (AMEME 2016), 2016, : 37 - 41
  • [46] GEOMETRICALLY CONSTRAINED INDEPENDENT VECTOR ANALYSIS FOR DIRECTIONAL SPEECH ENHANCEMENT
    Li, Li
    Koishida, Kazuhito
    2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2020, : 846 - 850
  • [47] Maximum Independent Component Analysis with Application to EEG Data
    Guo, Ruosi
    Zhang, Chunming
    Zhang, Zhengjun
    STATISTICAL SCIENCE, 2020, 35 (01) : 145 - 157
  • [48] Independent component analysis by lp-norm optimization
    Park, Sungheon
    Kwak, Nojun
    PATTERN RECOGNITION, 2018, 76 : 752 - 760
  • [49] Optimal Portfolio Diversification via Independent Component Analysis
    Lassance, Nathan
    DeMiguel, Victor
    Vrins, Frederic
    OPERATIONS RESEARCH, 2022, 70 (01) : 55 - 72
  • [50] Independent Component Analysis for Carrier Synchronization in OFDM Systems
    Luo, Zhongqiang
    Zhu, Lidong
    Li, Chengjie
    2014 SIXTH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2014,
12345