[Application of kalman filtering based on wavelet transform in ICP-AES].
Kalman filtering is a recursive algorithm, which has been proposed as an attractive alternative to correct overlapping interferences in ICP-AES. However, the noise in ICP-AES contaminates the signal arising from the analyte and hence limits the accuracy of kalman filtering. Wavelet transform is a powerful technique in signal denoising due to its multi-resolution characteristics. In this paper, first, the effect of noise on kalman filtering is discussed. Then we apply the wavelet-transform-based soft-thresholding as the pre-processing of kalman filtering. The simulation results show that the kalman filtering based on wavelet transform can effectively reduce the noise and increase the accuracy of the analysis.
Qin
Xia
X
Signal and Information Processing Lab, Beijing Polytechnic University, Beijing 100022, China.
Shen
Lan-sun
LS
D000465:Algorithms; D003198:Computer Simulation; D005374:Filtration; D012680:Sensitivity and Specificity; D013054:Spectrophotometry, Atomic / Q000379:methods*