A constrained Newton algorithm for maximum likelihood modeling of sums of exponentials, in noise

Author

George, J. ; Ainsleigh, P.

Author_Institution

Signalmetrics Inc., Winter Park, FL, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2443

Abstract

The problem of the estimation of stepped sine response parameters, for a system excited near a resonance is addressed. A novel Newton method is investigated for minimizing a variable projection functional which arises in the modeling of sums of exponentials in noise. The Hessian matrix is derived for the general variable projection functional, and a Newton algorithm which constrains the signal model to include poles at the excitation frequency and at DC is implemented. This algorithm achieves maximum-likelihood performance and offers a computational advantage when the number of data points is moderate to large or when the model order is small

Keywords

approximation theory; filtering and prediction theory; matrix algebra; parameter estimation; DC; Hessian matrix; constrained Newton algorithm; estimation; excitation frequency; maximum likelihood modeling; minimisation; noise; poles; prediction filter; resonant system; signal model; stepped sine response parameters; sums of exponentials; variable projection functional; Acoustic noise; Amplitude estimation; Convolution; Filters; Frequency; Frequency estimation; Maximum likelihood estimation; Newton method; Noise measurement; Resonance; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.116083

Filename

116083