FIR system identification for correlated noise using the convolution matrix, an investigation. Issue 6 (September 2016)

• Record Type: Journal Article
• Authors: Moir, T.
• Is Part Of: Signal, image and video processing. Volume 10:Issue 6(2016)
• Page Start: 1049
• Page End: 1054
• Publication Date: 2016-09
• Subjects: LMS -- Correlated -- Noise; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0857-2
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract A novel approach to finite-impulse response system identification is given. The method is formulated differently from ordinary least mean squares (LMS) or block LMS, which are traditional approaches and has a significant advantage of speed improvement when the correlation matrix has a large condition number. Unlike other approaches which are numerically complex, this method has a similar computational burden as LMS and gives the same optimal solution after convergence. It avoids transformation matrices by writing the system description in terms of a convolution matrix which has a special lower-triangular format. In this way the correlation matrix is different from conventional least-squares approaches and maintains a modest condition number as the correlation matrix in ordinary least-squares climbs high. The method has as wide a range of applications as ordinary LMS-based solutions but can also work on deterministic inputs.