Adaptive neural nets filter using a recursive Levenberg-Marquardt search direction
Paper i proceeding, 1998

This paper proposes a recursive Levenberg-Marquardt (LM) search direction as the training algorithm for non-linear adaptive filters, which use multi-layer feed forward neural nets as the filter structures. The neural nets can be considered as a class of non-linear adaptive filters with transversal or recursive filter structures. In the off-line training, the LM method is regarded as an intermediate method between the steepest descent (SD) and Gauss-Newton (GN) methods, and it has better convergence properties than the other two methods. In the echo cancellation experiments, the recursive LM algorithm converges faster and gives higher echo return loss enhancement (ERLE) than the recursive SD and GN algorithms.

Författare

Lester S.H. Ngia

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Jonas Sjöberg

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Mats Viberg

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Proc. Asilomar Conf. Signals, Systems, Computers, 01 Nov 1998-04 Nov 1998

Vol. 1 697-701

Ämneskategorier

Data- och informationsvetenskap

DOI

10.1109/ACSSC.1998.750952

Mer information

Skapat

2017-10-07