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

Namyong Kim, Hyung-Gi Byun, Ki-Hyeon Kwon, Krishna C. Persaud & Jeong-Ok Lim
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...