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EM-based identification of ARX systems having quantized output data
Conference ObjectAbstract: In this paper we develop a novel algorithm to identify an auto-regressive with exogenous signal systPalabras claves:Autores:Carvajal R., González K., 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 Filtering Methods for State-Space Systems having Binary Output Measurements
Conference ObjectAbstract: In this paper we develop two filtering algorithms for state-space systems with binary outputs. We apPalabras claves:Binary Quantizer, Gaussian Quadrature, Gaussian sum filter, particle Filter, State EstimationAutores:Albornoz R., Carvajal R., Cedeno A.L., Godoy B.I., Juan C. AgüeroFuentes: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: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:scopusModel error modelling using a stochastic embedding approach with gaussian mixture models for FIR systems
Conference ObjectAbstract: In this paper a Maximum Likelihood estimation algorithm for error-model modelling using a stochasticPalabras claves:Estimation, Expectation-maximization, Gaussian Mixture, Maximum likelihood, Model errors, Stochastic embeddingAutores:Carvajal R., Goodwin G.C., Juan C. Agüero, Orellana R.Fuentes:scopus