A fast algorithm for one-unit ICA-R

Qiu Hua Lin, Yong Rui Zheng, Fu Liang Yin, Hualou Liang, Vince D. Calhoun

Research output: Contribution to journalArticlepeer-review


Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. In some applications, it is preferable to extract only one desired source signal instead of all source signals, and this can be achieved by a one-unit ICA technique. ICA with reference (ICA-R) is a one-unit ICA algorithm capable of extracting an expected signal by using prior information. However, a drawback of ICA-R is that it is computationally expensive. In this paper, a fast one-unit ICA-R algorithm is derived. The reduction of the computational complexity for the ICA-R algorithm is achieved through (1) pre-whitening the observed signals; and (2) normalizing the weight vector. Computer simulations were performed on synthesized signals, a speech signal, and electrocardiograms (ECG). Results of these analyses demonstrate the efficiency and accuracy of the proposed algorithm.

Original languageEnglish (US)
Pages (from-to)1265-1275
Number of pages11
JournalInformation Sciences
Issue number5
StatePublished - Mar 1 2007
Externally publishedYes


  • Constrained independent component analysis
  • Independent component analysis
  • One-unit independent component analysis
  • Reference signal

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence


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