Title :
Denoising by local iterated extended Kalman filter for quantification purposes in electronic noses
Author :
Turmchokkasam, Sirichai ; Chamnongthai, Kosin
Author_Institution :
Dept. of Electron. & Telecommun. Eng., King Mongkuts Univ. of Technol. Thonburi, Bangkok, Thailand
Abstract :
In the area of electronic noses (e-noses), applications in the field of wine detection are uncommon. The number of qualified human wine experts is low and their cost is high. This paper has been developed for the purpose of local iterated extended Kalman filtering technique for collecting raw data (typical red wine aromas) and de-noising based on the output noise characteristics of those gas sensors. Compared to the conventional Kalman filter algorithm.
Keywords :
Kalman filters; beverages; electronic noses; iterative methods; nonlinear filters; signal denoising; e-nose; electronic nose; gas sensor; local iterated extended Kalman filtering technique; noise denoising; quantification purpose; raw data collection; wine detection; Covariance matrices; Electronic noses; Equations; Information technology; Jacobian matrices; Kalman filters; Sensors; Electronic Noses; Kalman Filter Algorithm; Local Iterated Extended Kalman Filtering Technique; Wine Aromas;
Conference_Titel :
Communications and Information Technologies (ISCIT), 2014 14th International Symposium on
Conference_Location :
Incheon
DOI :
10.1109/ISCIT.2014.7011921
