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Application of Rank-Constrained Optimisation to Nonlinear System Identification
Conference ObjectAbstract: Nonlinear System Identification has a rich history spanning at least 5 decades. A very flexible apprPalabras claves:Autores:Delgado R.A., Goodwin G.C., Juan C. Agüero, Mendes E.M.A.M.Fuentes:scopusEM-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: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:scopusGaussian Sum Filtering for Wiener State-Space Models with a Class of Non-Monotonic Piecewise Nonlinearities
OtherAbstract: State estimation of nonlinear dynamical systems has gained significant attention due to its countlesPalabras claves:Bayesian estimation, Gaussian sum filtering, Piecewise linear approximation, State Estimation, Wiener systemsAutores:Cedeno A.L., Juan C. Agüero, Rodrigo A. GonzálezFuentes:scopusA Bayesian Filtering Method for Wiener State-Space Systems Utilizing a Piece-wise Linear Approximation
OtherAbstract: In this paper, we develop a filtering algorithm for Wiener systems written in state-space form whichPalabras claves:Bayesian estimation, Gaussian sum filtering, Piece-wise linear approximation, State Estimation, Wiener systemsAutores:Carvajal R., Cedeno A.L., Juan C. Agüero, Orellana R.Fuentes:scopusAn Identification Method for Stochastic Continuous-time Disturbances in Adaptive Optics Systems
OtherAbstract: This paper presents a novel identification method for stochastic continuous-time systems applied toPalabras claves:Adaptive optics, Continuous-time systems, Disturbance modelling, Maximum likelihood, Sampled-data, Whittle's log-likelihoodAutores:Carvajal R., Coronel M., Escarate P., Juan C. Agüero, Orellana R.Fuentes:scopusAn EM Algorithm for Lebesgue-sampled State-space Continuous-time System Identification
OtherAbstract: This paper concerns the identification of continuous-time systems in state-space form that are subjePalabras claves:Continuous-time systems, event-based sampling, Expectation-maximization, system identificationAutores:Cedeno A.L., Coronel M., Juan C. Agüero, Rodrigo A. González, Rojas C.R.Fuentes:scopusModel Error Modeling and Stochastic Embedding
Conference ObjectAbstract: To estimate a model of useful complexity for control design, at the same time as having a good insigPalabras claves:Empirical Bayes, Error quantification, Model errorsAutores:Chen T., Goodwin G.C., Juan C. Agüero, Ljung L.Fuentes: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