By Topic

Exact maximum likelihood estimation of superimposed exponential signals in noise

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Bresler, Y. ; Stanford University, Stanford, CA ; Macovski, A.

A unified framework for the exact Maximum Likelihood estimation of the parameters of superimposed exponential signals in noise, encompassing both the single and the multiexperiment cases (respectively the time series and the array problems), is presented. An exact expression for the ML criterion is derived in terms of the prediction polynomial of the noiseless signal, and an iterative algorithm for the maximization of this criterion is presented. A simulation example shows the estimator to be capable of providing more accurate frequency estimates than currently existing techniques.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '85.  (Volume:10 )

Date of Conference:

Apr 1985