CIFASIS   20631
CENTRO INTERNACIONAL FRANCO ARGENTINO DE CIENCIAS DE LA INFORMACION Y DE SISTEMAS
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Identification of Wiener Models based on SVM and Orthonormal Bases
Autor/es:
GÓMEZ, JUAN CARLOS; BAEYENS, ENRIQUE
Lugar:
La Plata
Reunión:
Simposio; 13º Simposio Argentino de Tecnología (AST 2012); 2012
Institución organizadora:
SADIO: Sociedad Argentina de Informática, y Facultad de Informática de la UNLP
Resumen:
In this paper, a novel method for the identification of the
linear and nonlinear blocks in a Wiener model is presented. The method
combines Support Vector Machines and Least Squares Prediction Error
techniques. The identification is carried out by minimizing an augmented
cost function defined as the sum of the standard structural risk function
appearing in Support Vector Regression and the quadratic criterion on
the prediction errors associated to Least Squares estimation methods.
The properties of the proposed method are illustrated through simulation
examples.