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In this paper a Maximum likelihood estimation algorithm for Finite Impulse Response Errors-in-Variables systems is developed. We consider that the noise-free input signal is Gaussian-mixture distributed. We propose an Expectation-Maximization-based… Click to show full abstract
In this paper a Maximum likelihood estimation algorithm for Finite Impulse Response Errors-in-Variables systems is developed. We consider that the noise-free input signal is Gaussian-mixture distributed. We propose an Expectation-Maximization-based algorithm to estimate the system model parameters, the input and output noise variances, and the Gaussian mixture noise-free input parameters. The benefits of our proposal are illustrated via numerical simulations.
Keywords:
response errors;
mixture;
errors variables;
impulse response;
gaussian mixture;
finite impulse
Journal Title: IEEE Access
Year Published: 2023
Link to full text (if available)
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Journal Title: IEEE Access
Year Published: 2023
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!