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 language | English |
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Article number | 109937 |
Journal | Automatica |
Volume | 135 |
DOIs | |
State | Published - Jan 2022 |
Keywords
- Expectation–Maximization
- Gaussian mixture noise distribution
- Maximum likelihood
- Non-minimum-phase transfer function