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IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019(1)
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scopus(3)
On 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 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:scopus