Title :
Globally Convergent Deflationary Instantaneous Blind Source Separation Algorithm for Digital Communication Signals
Author :
Erdogan, Alper Tunga
Author_Institution :
Electr. & Electron. Eng. Dept., Koc Univ., Istanbul
fDate :
5/1/2007 12:00:00 AM
Abstract :
Recently an instantaneous blind source separation (BSS) approach that exploits the bounded magnitude structure of digital communications signals has been introduced. In this paper, we introduce a deflationary adaptive algorithm based on this criterion and provide its convergence analysis. We show that the resulting algorithm is convergent to one of the globally optimal points that correspond to perfect separation. The simulation examples related to the separation of digital communication signals are provided to illustrate the convergence and the performance of the algorithm
Keywords :
blind source separation; digital communication; matrix algebra; bounded magnitude structure; deflationary adaptive algorithm; digital communication signals; instantaneous blind source separation algorithm; Adaptive algorithm; Blind source separation; Convergence; Cost function; Digital communication; H infinity control; Minimization methods; Particle separators; Source separation; Vectors; Adaptive filtering; blind source separation (BSS); independent component analysis; multiple-in multiple-out (MIMO) blind equalization; subgradient;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.893214