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Proceedings Paper

An analysis of self-organization process for data classification in multisensor systems
Author(s): Slawomir Przylucki; Waldemar Wojcik; Konrad Plachecki; Tomasz Golec
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Paper Abstract

In this paper we present the idea of the optoelectronic measurement system for monitoring the industrial gas pollutants. The system consists of an optical detection system, an optical fiber as a data transmission link, a spectrometer with linear diode array and a neural network unit for real-time spectral data processing. We paid main attention to the neural network structure and its properties for gas recognition and gas concentration estimation task. The article presents the new classification algorithm based on the selforganizing artificial neural network. The algorithm comes from the kohonen selforganizing neural net idea. It introduces the groups of winners and that is why, we call it Multi-Winners Selforganizing Kohonen Map - MWSOM. The behavior and fundamental featured of that classifier are presented and verified by comparison to other 'classical' classification algorithms.

Paper Details

Date Published: 22 September 2003
PDF: 8 pages
Proc. SPIE 5124, Optoelectronic and Electronic Sensors V, (22 September 2003); doi: 10.1117/12.517138
Show Author Affiliations
Slawomir Przylucki, Technical Univ. of Lublin (Poland)
Waldemar Wojcik, Technical Univ. of Lublin (Poland)
Konrad Plachecki, Technical Univ. of Lublin (Poland)
Tomasz Golec, Institute of Power Industry (Poland)

Published in SPIE Proceedings Vol. 5124:
Optoelectronic and Electronic Sensors V
Wlodzimierz Kalita, Editor(s)

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