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Proceedings Paper

Adaptive sensor for chemical analysis
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Paper Abstract

Using our experience in signal processing and optimization of complex systems we propose a new method to adaptive sensing of chemical content of vegetations. This framework is demonstrated for different agricultural plants using the neural network algorithm for classification of spectral curves and adaptive filtration. Utilization of characteristics of leaf reflectance spectrum, which are a relative characteristic of the light reflected from canopies, makes it possible to avoid the necessity of measuring the 100% reflectance standard and to provide the high resistance of the method to distorting factors in particular to soil reflectance contribution. For utilization of the method the numerical algorithms is proposed. Various estimation problems will be considered to illustrate the computational aspects of the proposed method. The software is based on digital filter, optimization approach and neural network algorithm for classification of chemical components. Supporting software for data management, storage, signal processing will be development. A concept of an intelligent sensor is considered.

Paper Details

Date Published: 15 August 2003
PDF: 10 pages
Proc. SPIE 5085, Chemical and Biological Sensing IV, (15 August 2003); doi: 10.1117/12.485730
Show Author Affiliations
Panos M. Pardalos, Univ. of Florida (United States)
Vitaliy Alexeevich Yatsenko, Scientific Foundation of Researchers and Specialists on Molecular Cybernetics and Informatics (Ukraine)
Svetlana M. Kochubey, Institute of Plant Physiology and Genetics (Ukraine)
Lezhou Zhan, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 5085:
Chemical and Biological Sensing IV
Patrick J. Gardner, Editor(s)

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