Title :
Hybrid LMS-LMF algorithm for adaptive echo cancellation
Author :
Zerguine, A. ; Bettayeb, M. ; Cowan, C.F.N.
Author_Institution :
Dept. of Phys., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
fDate :
8/1/1999 12:00:00 AM
Abstract :
The coefficients of an echo canceller with a near-end section and a far-end section are usually updated with the same updating scheme, such as the LMS algorithm. A novel scheme is proposed for echo cancellation that is based on the minimisation of two different cost functions, i.e. one for the near-end section and a different one for the far-end section. The approach considered leads to a substantial improvement in performance over the LMS algorithm when it is applied to both sections of the echo canceller. The convergence properties of the algorithm are derived. The proposed scheme is also shown to be robust to noise variations. Simulation results confirm the superior performance of the new algorithm
Keywords :
Gaussian processes; adaptive filters; adaptive signal processing; echo suppression; filtering theory; least mean squares methods; Gaussian environment; LMS algorithm; adaptive echo cancellation; adaptive filters; convergence properties; cost functions minimisation; echo canceller coefficients; far-end section; hybrid LMS-LMF algorithm; least mean fourth algorithm; near-end section; noise variations; nonGaussian environment; performance; simulation results; updating scheme;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:19990468