This paper studies a method for the identification of Hammerstein models based on Least Squares Support Vector Machines (LS-SVMs). The technique allows for the determination of th...
Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Su...
In the identification of nonlinear dynamical models it may happen that not only the system dynamics have to be modeled but also the noise has a dynamic character. We show how to ad...
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...