The Parzen kernel approach to learning in non-stationary environment
Lena Pietruczuk, Leszek Rutkowski, Maciej Jaworski, Piotr Duda · 2014
In this paper a method for nonparametric regression estimation in non-stationary environment is presented. The Parzen kernels are used to design the recursive general regression neural networks to track changes of non-stationary system under non-stationary noise. The probabilistic properties of the proposed method are investigated. Experimental results are presented and discussed.