Title :
Parameter Optimization Methods for the EDS Model
Author :
Lamens, Stijn ; Haes, Wim D.
Author_Institution :
Vision Lab, Antwerp Univ.
Abstract :
Various methods have been proposed to estimate the parameters of the exponentially damped sinusoidal (EDS) model. As most estimation methods do not yield optimal parameter values, it is often useful to apply further optimization. In this work, various optimization algorithms which can be used for both frequency and damping factor parameters are developed and compared. The optimization methods include Newton and Gauss-Newton methods, which were improved by applying a regularization factor resulting in the Levenberg-Marquardt method. Estimation and optimization algorithms were implemented and tested in two different methodologies: a method where optimization is performed on all partials simultaneously, and a pseudo-simultaneous method where optimization is performed on individual partials in an iterative manner
Keywords :
Gaussian processes; Newton method; audio signal processing; optimisation; EDS model; Gauss-Newton methods; Levenberg-Marquardt method; audio signals; damping factor parameters; exponentially damped sinusoidal model; iterative manner; parameter optimization methods; pseudo-simultaneous method where; Damping; Frequency; Iterative algorithms; Least squares methods; Newton method; Optimization methods; Parameter estimation; Performance evaluation; Recursive estimation; Yield estimation;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660695