ARMA model identification from noisy observations based on a two-step errors-in-variables approach
Sign Up to like & getrecommendations! Published in 2017 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2017.08.1857
Abstract: Abstract This paper proposes a new method for identifying ARMA models in the presence of additive white noise. The method operates with two main steps. First, the noisy ARMA model is approximated by the sum… read more here.
Keywords: variables approach; errors variables; arma model; model ... See more keywords
On maximum likelihood identification of errors-in-variables models
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DOI: 10.1016/j.ifacol.2017.08.634
Abstract: Abstract In this paper, we revisit maximum likelihood methods for identification of errors-in-variables systems. We assume that the system admits a parametric description, and that the input is a stochastic ARMA process. The cost function… read more here.
Keywords: errors variables; maximum likelihood; variables models; likelihood identification ... See more keywords
Non-Asymptotic Confidence Regions for Errors-In-Variables Systems
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DOI: 10.1016/j.ifacol.2018.09.060
Abstract: Abstract This paper deals with constructing non-asymptotic confidence regions for Errors-In-Variables (EIV) systems when there is noise on both the input and the output signal. The Leave-out Sign-dominant Correlation Regions (LSCR) approach originally devised for… read more here.
Keywords: errors variables; confidence; regions errors; confidence regions ... See more keywords
Statistical estimation for a partially linear single-index model with errors in all variables
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DOI: 10.1080/03610926.2018.1425446
Abstract: ABSTRACT This article considers partially linear single-index models with errors in all variables. By using the Pseudo − θ method (Liang, Härdle, and Carroll 1999), local linear regression and simulation-extrapolation (SIMEX) technique (Cook and Stefanski… read more here.
Keywords: errors variables; linear single; model; single index ... See more keywords
Estimation on semi-functional linear errors-in-variables models
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DOI: 10.1080/03610926.2018.1494836
Abstract: Abstract Semi-functional linear regression models are important in practice. In this paper, their estimation is discussed when function-valued and real-valued random variables are all measured with additive error. By means of functional principal component analysis… read more here.
Keywords: semi functional; errors variables; functional linear; variables models ... See more keywords
Finite Impulse Response Errors-in-Variables System Identification Utilizing Approximated Likelihood and Gaussian Mixture Models
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DOI: 10.1109/access.2023.3255827
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… read more here.
Keywords: response errors; mixture; errors variables; impulse response ... See more keywords
Non-asymptotic Confidence Regions for the Transfer Functions of Errors-in-Variables Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2021.3080504
Abstract: Finite-sample system identification (FSID) methods provide guaranteed confidence regions for the unknown model parameter of dynamical systems under mild statistical assumptions for a finite number of data points. In this article, two FSID methods, the… read more here.
Keywords: non asymptotic; confidence; errors variables; eiv systems ... See more keywords
Robust Global Identification of LPV Errors-in-Variables Systems With Incomplete Observations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3071137
Abstract: This article develops a robust global strategy for identifying the linear parameter varying (LPV) errors-in-variables (EIVs) systems subjected to randomly missing observations and outliers. The parameter interpolated LPV autoregressive exogenous model with an uncertain/noisy input… read more here.
Keywords: errors variables; identification; robust global; identification lpv ... See more keywords