P2.9.33 Unsupervised adjustment of centers in RBF networks for sensor drift compensation

Event
14th International Meeting on Chemical Sensors - IMCS 2012
2012-05-20 - 2012-05-23
Nürnberg/Nuremberg, Germany
Chapter
P2.9 Technology and Application
Author(s)
N. Kim, H. Byun, K. Kwon - School of Electronics, Information & Communication Engineering, Kangwon National University (Korea), K. Persaud - School of Chemical Engineering and Analytical Science, The University of Manchester (U.K.), J. Lim - Biomedical Research Institute, Kyungpook National University (Korea)
Pages
1802 - 1804
DOI
10.5162/IMCS2012/P2.9.33
ISBN
978-3-9813484-2-2
Price
free

Abstract

In our previous research for sensor drift compensation, the unsupervised signal processing approach of readjusting the weights of Radial Basis Function Network (RBFN) based on probability distribution functions (PDFs) has shown a possibility to solve the sensor drift problems, but it was not satisfactory still showing deteriorated distributions in some gases. In this paper, a new readjustment method for another parameter, center of RBFN based on PDFs is proposed for sensor drift compensation. Compared to the case of weight readjustment only, the proposed method yields significantly decreased dispersions for most gases and even for the ones deteriorated after weight readjustment. This proves the proposed method for additional center readjustment to be more effective in sensor drift compensation.