The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Fast adaptive algorithms for signal separation
Author:	Manzo, Robert A.
View Online:	njit-etd1994-106 (xii, 78 pages ~ 5.6 MB pdf)
Department:	Department of Electrical and Computer Engineering
Degree:	Master of Science
Program:	Electrical Engineering
Document Type:	Thesis
Advisory Committee:	Haimovich, Alexander (Committee chair) Ansari, Nirwan (Committee member) Siveski, Zoran (Committee member)
Date:	1994-05
Keywords:	Adaptive signal processing. Least squares.
Availability:	Unrestricted
Abstract:	LMS and RLS type algorithms are suggested for decorrelation of multi-channel systems outputs. These algorithms act as signal separators when applied to unknown linear combinations of the inputs. The performance of the suggested algorithms is compared with that of the conventional LMS and RLS algorithms that minimize the mean square error. It. is shown that the correlation matrix eigenvalue spread associated with the LMS decorrelator is always smaller than the eigenvalue spread corresponding to the conventional LMS. resulting in faster convergence speed for the decorrelator. A new RLS type decorrelator algorithm is suggested. The RLS decorrelator is shown to be faster than the LMS decorrelator. not affected by the eigenvalue spread, and comparable in speed with the conventional RLS algorithm. Convergence analysis by simulation shows that the RLS algorithms and the LMS decorrelator have wider regions of convergence than the conventional LMS.