By Topic

A new log-likelihood gradient formula for continuous time stochastic systems with uncertain matrix

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

1 Author(s)
Leland, R.P. ; Dept. of Electr. Eng., Alabama Univ., Tuscaloosa, AL, USA

We use a finitely additive white noise approach to derive an explicit expression for the gradient of the log-likelihood ratio for system parameter estimation in the case of a continuous time linear dynamic stochastic system and noisy observations. Our gradient formula, includes the smoother estimates of the state, and derivatives of the system matrices, but no derivatives of the estimates or error covariances. A scheme to calculate the log-likelihood gradient without solving any Ricatti equations is described

Published in:

Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on  (Volume:3 )

Date of Conference:

14-16 Dec 1994