Automatic indexing system for atmospheric laser radar data

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Abstract

The purpose of this paper is to design a new method for an automatic indexing system with unsupervised conditions. In this paper, the method of a self-organizing clustering network is adopted. It is used to classify and index a large amount of real atmospheric laser radar data. Initially, the parameters of each cluster will start with random initial values and are adapted with the algorithm. In this paper, six groups are clustered from the given data. It is also shown that some of these indicate quite important atmospheric condition characteristics.

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Aerosols, Artificial neural networks, Atmosphere, Atmospheric measurements, Laser radar, Machine assisted indexing, Optical scattering, Radar imaging, Radar remote sensing, Radar scattering

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IEEE Asia Pacific Conference on Circuits and Systems Proceedings Apccas, 2, 237-240, 2002

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