Statistical Learning for Systems Modeling

The work presented in this report falls within the framework of Machine Learning where we seek to model a non-linear system and to identify online the parameters of the model considered. This model is developed in a reproducing kernel Hilbert space (RKHS). These so-called representation or black box models are linear with respect to their parameters. They have had great success in identifying nonlinear systems using kernel methods.