Naslov
Analysis of Low Rank Transform Domain Adaptive Filtering Algorithm

Autori
Raghothaman, Balaji ; Linebarger, Darel ; Begušić, Dinko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the International Conference on Acoustics, Speech and Signal Processing ICASSP '99 / Rodriguez, Jeffrey - Piscataway (NJ) : Institute of Electrical and Electronics Engineers (IEEE), 1999, 1869-1872

Skup
1999 IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP '99

Mjesto i datum
Phoenix (AZ), Sjedinjene Američke Države, 15.03.1999. - 19.03.1999

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
adaptive filtering; transform domain; low rank; SVD; DFT; Affine Projection

Sažetak
The paper analyzes an SVD based low rank transform domain adaptive filtering algorithm and proves that it performs better than Normalized LMS. The method extracts an underdetermined solution from an overdetermined least squares problem, using a part of the unitary transformation formed by the right singular vectors of the data matrix. The aim is to get as close to the solution of an overdetermined system as possible, using an underdetermined system. Previous work based on the same framework, but with the DFT as the transformation, has shown considerable improvement in performance over conventional time domain methods like NLMS and Affine Projection. The analysis of the SVD-based variant helps us to understand the convergence behaviour of the DFT-based low complexity method. We prove that the SVD-based method gives a lower residual than NLMS. Simulations confirm the theoretical results.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika

POVEZANOST RADA