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

Rafael Orellana, Gustavo Bittner, Rodrigo Carvajal, Juan C. Agüero

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Article number109937
JournalAutomatica
Volume135
DOIs
StatePublished - Jan 2022
Externally publishedYes

Keywords

  • Expectation–Maximization
  • Gaussian mixture noise distribution
  • Maximum likelihood
  • Non-minimum-phase transfer function

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