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- Abdalmoaty, Mohamed Rasheed,1986-KTH, Reglerteknik (author)
A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems
- Article/chapterEnglish2016
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- IEEE,2016
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- LIBRIS-ID:oai:DiVA.org:uu-474175
- https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-474175URI
- https://doi.org/10.1109/CDC.2016.7798727DOI
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- Language:English
- Summary in:English
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- This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.
Subject headings and genre
- TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Signalbehandling hsv//swe
- ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing hsv//eng
- Electrical Engineering
- Elektro- och systemteknik
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- Hjalmarsson, HåkanKTH, Reglerteknik (author)
- KTH, Reglerteknik (creator_code:org_t)
Related titles
- In:2016 IEEE 55th Conference on Decision and Control (CDC): IEEE, s. 3060-3065978150901837697815090184449781509018383
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