Finite Impulse Response Errors-in-Variables System Identification Utilizing Approximated Likelihood and Gaussian Mixture Models

Finite Impulse Response Errors-in-Variables System Identification Utilizing Approximated Likelihood and Gaussian Mixture Models

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,...

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Bibliographic Details
Main Authors: Angel L. Cedeno, Rafael Orellana, Rodrigo Carvajal, Boris I. Godoy, Juan C. Aguero
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Errors-in-variables
maximum likelihood
expectation-maximization
Gaussian mixture distribution
estimation
Online Access:https://ieeexplore.ieee.org/document/10065424/

Internet

https://ieeexplore.ieee.org/document/10065424/

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