Maximum Likelihood estimation for non-minimum-phase noise transfer function with Gaussian mixture noise distribution

In this paper a Maximum Likelihood estimation algorithm for a linear dynamic system driven by an exogenous input signal, with non-minimum-phase noise transfer function and a Gaussian mixture noise is developed. We propose a flexible identification technique to estimate the system model parameters an...

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Veröffentlicht in:Automatica (Oxford) 2022-01, Vol.135, p.109937, Article 109937
Hauptverfasser: Orellana, Rafael, Bittner, Gustavo, Carvajal, Rodrigo, Agüero, Juan C.
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Sprache:eng
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Zusammenfassung:In this paper a Maximum Likelihood estimation algorithm for a linear dynamic system driven by an exogenous input signal, with non-minimum-phase noise transfer function and a Gaussian mixture noise is developed. We propose a flexible identification technique to estimate the system model parameters and the Gaussian mixture parameters based on the Expectation–Maximization algorithm. The benefits of our proposal are illustrated via numerical simulations.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2021.109937