Title :
The Parzen kernel approach to learning in non-stationary environment
Author :
Pietruczuk, Lena ; Rutkowski, Leszek ; Jaworski, M. ; Duda, Piotr
Author_Institution :
Inst. of Comput. Intell., Czestochowa Univ. of Technol., Czestochowa, Poland
Abstract :
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.
Keywords :
learning (artificial intelligence); neural nets; regression analysis; Parzen kernel approach; learning approach; nonparametric regression estimation; nonstationary learning environment; nonstationary noise; recursive general regression neural networks; Convergence; Data mining; Kernel; Learning systems; Neural networks; Noise; Probabilistic logic;
Conference_Titel :
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6627-1
DOI :
10.1109/IJCNN.2014.6889805
