DocumentCode
1798152
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
fYear
2014
fDate
6-11 July 2014
Firstpage
3319
Lastpage
3323
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889805
Filename
6889805
Link To Document