Abstract
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. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
