Sparse Estimation of Polynomial and Rational Dynamical Models

In many practical situations, it is highly desirable to estimate an accurate mathematical model of a real system using as few parameters as possible. At the same time, the need for an accurate description of the system behavior without knowing its complete dynamical structure often leads to model pa...

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Vydané v:	IEEE transactions on automatic control Ročník 59; číslo 11; s. 2962 - 2977
Hlavní autori:	Rojas, Cristian R., Toth, Roland, Hjalmarsson, Hakan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	AIC BIC Biological system modeling Cost function cross-validation Data models Dynamical systems Dynamics Economic models Estimates Estimation LASSO Linear regression Mathematical models model structure selection Noise Norms Parametrization Polynomials Regularization Simulation sparse estimation Sparsity Steiglitz-McBride method system identification sparse estimation Steiglitz-McBride method model structure selection LASSO cross-validation AIC system identification BIC
ISSN:	0018-9286, 1558-2523, 1558-2523
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