Abstract
Purpose Here, we present a general methodology for solving problems of filtering, smoothing, and prediction, along with that of identifying transfer functions. For this, we use a Bayesian approach, which allows possible a priori information about the desired parameters to be incorporated. In order to be able to perform the numerical computation of the estimators, we use Monte Carlo techniques to solve integration and maximisation problems that appear in Bayesian estimation.
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© 2002 Springer-Verlag London
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Chonavel, T. (2002). Bayesian Methods and Simulation Techniques. In: Statistical Signal Processing. Advanced Textbooks in Control and Signal Processing. Springer, London. https://doi.org/10.1007/978-1-4471-0139-0_15
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DOI: https://doi.org/10.1007/978-1-4471-0139-0_15
Publisher Name: Springer, London
Print ISBN: 978-1-85233-385-0
Online ISBN: 978-1-4471-0139-0
eBook Packages: Springer Book Archive