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An identification method for Errors-in-Variables systems using incomplete data
Conference ObjectAbstract: In this paper we develop a novel identification algorithm for Errors-in-Variables systems (representPalabras claves:Errors-in-Variables systems, Frequency domain identification, Incomplete data, Maximum likelihood, system identificationAutores:Carvajal R., Delgado R.A., Goodwin G.C., Juan C. AgüeroFuentes:scopusEM-based identification of static errors-in-variables systems utilizing Gaussian Mixture models
Conference ObjectAbstract: In this paper we address the problem of identifying a static errors-in-variables system. Our proposaPalabras claves:Errors-in-Variables, Estimation, Expectation-maximization, Gaussian Mixture, Maximum likelihood, OptimizationAutores:Carvajal R., Cedeno A.L., Juan C. Agüero, Orellana R.Fuentes:scopusOn maximum likelihood estimation of continuous-time oscillators modelled as continuous-time autoregressive system
ArticleAbstract: In this paper, we address the problem of identifying a continuous-time oscillator. We use a continuoPalabras claves:Adaptive optics, continuous-time model, Maximum likelihood, Oscillators identification, VibrationsAutores:Carvajal R., Coronel M., Escarate P., González K., Juan C. AgüeroFuentes:scopusOn the uncertainty identification for linear dynamic systems using stochastic embedding approach with gaussian mixture models
ArticleAbstract: In control and monitoring of manufacturing processes, it is key to understand model uncertainty in oPalabras claves:Expectation-maximization, Gaussian Mixture Model, Maximum likelihood, Stochastic embedding, Uncertainty modelingAutores:Carvajal R., Escarate P., Juan C. Agüero, Orellana R.Fuentes:scopusOn the uncertainty modelling for linear continuous-time systems utilising sampled data and Gaussian mixture models
Conference ObjectAbstract: In this paper a Maximum Likelihood estimation algorithm for model error modelling in a continuous-tiPalabras claves:continuous-time model, Discrete-time model, Gaussian Mixture Model, Maximum likelihood, Stochastic embeddingAutores:Carvajal R., Coronel M., Delgado R.A., Escarate P., Juan C. Agüero, Orellana R.Fuentes:scopusMaximum Likelihood Infinite Mixture Distribution Estimation Utilizing Finite Gaussian Mixtures<sup>⁎</sup>
Conference ObjectAbstract: In this paper we develop a Maximum Likelihood estimation algorithm for the estimation of infinite miPalabras claves:Estimation, Expectation-maximization, Gaussian Mixture, Maximum likelihood, OptimizationAutores:Carvajal R., Juan C. Agüero, Orellana R.Fuentes:scopusMaximum Likelihood estimation for non-minimum-phase noise transfer function with Gaussian mixture noise distribution
ArticleAbstract: In this paper a Maximum Likelihood estimation algorithm for a linear dynamic system driven by an exoPalabras claves:Expectation–Maximization, Gaussian mixture noise distribution, Maximum likelihood, Non-minimum-phase transfer functionAutores:Bittner G., Carvajal R., Juan C. Agüero, Orellana R.Fuentes:scopusMaximum Likelihood identification for Linear Dynamic Systems with finite Gaussian mixture noise distribution
Conference ObjectAbstract: This paper considers the identification of a linear dynamic system driven by a non-Gaussian noise diPalabras claves:Gaussian Mixture Model, Linear Dynamical Systems, Maximum likelihood, Non-Gaussian Noise DistributionAutores:Bittner G., Carvajal R., Juan C. Agüero, Orellana R.Fuentes:scopusIdentification of continuous-time systems utilising Kautz basis functions from sampled-data
Conference ObjectAbstract: In this paper we address the problem of identifying a continuous-time deterministic system utilisingPalabras claves:continuous-time model, Discrete-time model, Kautz basis functions, Maximum likelihood, system identificationAutores:Carvajal R., Coronel M., Juan C. AgüeroFuentes:scopusIdentification of sparse FIR systems using a general quantisation scheme
ArticleAbstract: This paper presents an identification scheme for sparse FIR systems with quantised data. We considerPalabras claves:Maximum likelihood, Quantised systems, sparsity, system identificationAutores:Carvajal R., Godoy B.I., Goodwin G.C., Juan C. Agüero, Yuz J.I.Fuentes:scopus