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.