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.

翻译：本文提出一种正则化递推辨识算法，能同时在线估计模型参数与算法超参数。为促进算法开发，提出一种新核函数。通过仿真实验，将该新方案的性能与递推最小二乘算法进行对比。