%0 Conference Proceedings %T Recursive Least Squares algorithm dedicated to early recognition of explosive compounds thanks to multi-technology sensors %+ Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS) %A Mayoue, A. %A Martin, A. %A Lebrun, G. %A Larue, A. %Z Conference of 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference Date: 26 May 2013 Through 31 May 2013; Conference Code:101421 %< avec comité de lecture %( IEEE Xplore %B 2013 IEEE International Conference on Acoustics, Speech and Signal Processing %C Vancouver, BC, Canada %P 8761-8765 %8 2013-05-26 %D 2013 %R 10.1109/ICASSP.2013.6639377 %K Electronic NOSE %K Explosive compounds %K Multi-dimensional analysis %K Optimal conditions %K Real-time identification %K Recursive least square (RLS) %K Recursive least squares algorithms %K Volatile compounds %K Algorithms %K Explosives %K Pattern recognition %K Sensors %K Signal processing %K Volatile organic compounds %K Explosives detection %Z Engineering Sciences [physics]/Signal and Image processing %Z Chemical Sciences/Cheminformatics %Z Chemical Sciences/Analytical chemistry %Z Statistics [stat]/Methodology [stat.ME]Conference papers %X In this paper, a novel gas identification approach based on the Recursive Least Squares (RLS) algorithm is proposed. We detail some adaptations of RLS to be applied to a sensor matrix of several technologies in optimal conditions. The low complexity of the algorithm and its ability to process online samples from multi-sensor make the real-time identification of volatile compounds possible. The effectiveness of this approach to early detect and recognize explosive compounds in the air has been successfully demonstrated on an experimentally obtained dataset. %G English %L cea-01830772 %U https://cea.hal.science/cea-01830772 %~ CEA %~ DRT %~ LIST %~ DM2I %~ DIN