  This paper presents a regularized recursive identification algorithm with
simultaneous on-line estimation of both the model parameters and the algorithms
hyperparameters. A new kernel is proposed to facilitate the algorithm
development. The performance of this novel scheme is compared with that of the
recursive least squares algorithm in simulation.
