Recurrent online kernel recursive least square algorithm for nonlinear modeling

@article{Fan2012RecurrentOK,
  title={Recurrent online kernel recursive least square algorithm for nonlinear modeling},
  author={Haijin Fan and Qing Hai Song and Zhao Xu},
  journal={IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society},
  year={2012},
  pages={1574-1579}
}
In this paper, we proposed a recurrent kernel recursive least square (RLS) algorithm for online learning. In classical kernel methods, the kernel function number grows as the number of training sample increases, which makes the computational cost of the algorithm very high and only applicable for offline learning. In order to make the kernel methods suitable for online learning where the system is updated when a new training sample is obtained, a compact dictionary (support vectors set) should… CONTINUE READING