TY - GEN
T1 - Maximum Likelihood identification for Linear Dynamic Systems with finite Gaussian mixture noise distribution
AU - Bittner, Gustavo
AU - Orellana, Rafael
AU - Carvajal, Rodrigo
AU - Aguero, Juan C.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - This paper considers the identification of a linear dynamic system driven by a non-Gaussian noise distribution. The noise is approximated by a finite Gaussian mixture, whilst the parameters of the system and the parameters that approximate the noise distribution are simultaneously estimated using the principle of Maximum Likelihood. To this end, a global optimization algorithm is utilized to solve the resulting non-convex optimization problem. It is shown that our approach improves the accuracy of the estimates, when compared with classic estimation techniques such as the prediction error method (PEM), in terms of covariance of the estimation error, while also obtaining an approximation of the noise distribution. The benefits of the proposed technique are illustrated by numerical simulations.
AB - This paper considers the identification of a linear dynamic system driven by a non-Gaussian noise distribution. The noise is approximated by a finite Gaussian mixture, whilst the parameters of the system and the parameters that approximate the noise distribution are simultaneously estimated using the principle of Maximum Likelihood. To this end, a global optimization algorithm is utilized to solve the resulting non-convex optimization problem. It is shown that our approach improves the accuracy of the estimates, when compared with classic estimation techniques such as the prediction error method (PEM), in terms of covariance of the estimation error, while also obtaining an approximation of the noise distribution. The benefits of the proposed technique are illustrated by numerical simulations.
KW - Gaussian Mixture Model
KW - Linear Dynamical Systems
KW - Maximum Likelihood
KW - Non-Gaussian Noise Distribution
UR - http://www.scopus.com/inward/record.url?scp=85081063893&partnerID=8YFLogxK
U2 - 10.1109/CHILECON47746.2019.8987642
DO - 10.1109/CHILECON47746.2019.8987642
M3 - Conference contribution
AN - SCOPUS:85081063893
T3 - IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
BT - IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
Y2 - 13 November 2019 through 27 November 2019
ER -