Blind Source Separation: Fundamentals and Recent Advances (A Tutorial Overview Presented at SBrT-2001)

TL;DR

This tutorial provides an overview of blind source separation (BSS), covering fundamental concepts, traditional methods, recent advances, and their applications across various fields, emphasizing a unified presentation of different approaches.

Contribution

It offers a comprehensive tutorial that unifies well-known and recent BSS methods, highlighting their similarities, differences, and relative advantages in a clear, accessible manner.

Findings

Summarizes key BSS algorithms and their comparative advantages.

Highlights recent developments and trends in BSS research.

Provides a structured overview to facilitate understanding of BSS fundamentals.

Abstract

Blind source separation (BSS), i.e., the decoupling of unknown signals that have been mixed in an unknown way, has been a topic of great interest in the signal processing community for the last decade, covering a wide range of applications in such diverse fields as digital communications, pattern recognition, biomedical engineering, and financial data analysis, among others. This course aims at an introduction to the BSS problem via an exposition of well-known and established as well as some more recent approaches to its solution. A unified way is followed in presenting the various results so as to more easily bring out their similarities/differences and emphasize their relative advantages/disadvantages. Only a representative sample of the existing knowledge on BSS will be included in this course. The interested readers are encouraged to consult the list of bibliographical references for more details on this exciting and always active research topic.