DocumentCode
532292
Title
Information fusion technology on signal analysis of chrysanthemum coronarium
Author
Wang, Lanzhou ; Li, Qiao
Author_Institution
Coll. of Life Sci., China Jiliang Univ., Hangzhou, China
Volume
1
fYear
2010
fDate
22-24 Oct. 2010
Abstract
The information fusion technology was used for processing plant electrical signals. Weak electrical signals of the plant were tested by a touching test system of self-made double shields with platinum sensors. Tested data of electrical signals were denoised with the wavelet soft threshold. A novel autoregressive integrated moving average (ARIMA) model of weak electric signals of Chrysanthemum coronarium was constructed by the information fusion technology for the first time, that is, X t =1.86218X t-1 - 0.86218X t-2 +εt + 0.28666et-1 - 0.22095X t-2 - 0.11509X t-3 - 0.13495X t-4. A fitting standard deviation was 0.67622. It has a well effect that the fitting variance and standard deviation of the model are the minimum. It is very importance that the plant electric signal with the data fusion is to understand self-adapting regulations on the growth relationship between the plant and environments. The forecast data can be used as preferences for the intelligent system on the adaptive characters of plants.
Keywords
autoregressive moving average processes; botany; medical signal processing; sensor fusion; sensors; signal denoising; wavelet transforms; ARIMA model; autoregressive integrated moving average model; chrysanthemum coronarium; electrical signal denoising; fitting variance; information fusion technology; intelligent system; plant electrical signals; platinum sensors; self-adapting regulations; self-made double shields; signal analysis; standard deviation; touching test system; wavelet soft threshold; weak electric signals; ARIMA model; Chrysanthemum coronarium; information fusion; weak electrical signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Electronic_ISBN
978-1-4244-7237-6
Type
conf
DOI
10.1109/ICCASM.2010.5620285
Filename
5620285
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