Blind source separation with modified ICA

Shih Lin Lin, Pi Cheng Tung

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Blind source separation is an important but highly challenging technology in many fields of applied sciences. Independent Component Analysis (ICA) is a technology that incorporates statistics, computer science, and digital signal processing. In the separation of blind sources under multiple sensors, ICA is able to estimate approximately the types of signal. This study proposed a modified ICA method which can estimate the actual phase and amplitude and retrieve the signals separated by blind source separation to its original state. This method has great potential for application in diverse fields.

Original languageEnglish
Pages (from-to)364-371
Number of pages8
JournalWSEAS Transactions on Communications
Issue number2
StatePublished - Feb 2007


  • Blind source separation
  • Computer science
  • Independent component analysis


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