ICANN 98 pp 269-274 | Cite as

TDNN Approach to Measuring Raindrop Sizes and Velocities

  • Bruce Denby
  • Peter Golé
  • Jerôme Tarniewicz
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

The paper describes a TDNN solution to a signal processing problem in the meteorological and telecommunications domains. Optical disdrometers measure raindrop sizes and velocites by registering changes in photodiode current as the droplets pass through a collimated light beam. In an improved dual-beam device being built at CETP, feature extraction MLPs applied to 20-sample windows of photodiode current provide input to a higher-level network which reconstructs droplet velocities and diameters in real time. In tests on simulated data, measurement precision is quite good for droplets as small as .05 mm radius. The algorithm can be executed either directly on the acquisition PC, or on a neural net coprocessor for additional speedup.

Keywords

Microwave Extractor 

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References

  1. [1]
    D. Hauser, P. Amayenc, B. Nutten, and P. Waldteufel, 1984: A New Optical Instrument for Simultaneous Measurement of Raindrop Diameter and Fall Speed Distribution, J. Atmos. Ocean. Technol., 1, Nr. 3, 256–245.CrossRefGoogle Scholar
  2. [2]
    B. Denby, P. Gole, A. Sartori, G. Tecchiolli, Real Time Data Acquisition Techniques in Meteorological Applications, IEEE Transactions on Nuclear Science, in press, 1998.Google Scholar
  3. [3]
    A. Sartori and G. Tecchiolli: TOTEM, A Digital Processor for Neural Networks and Reactive Tabu Search, Data Sheet, August, 1995, IRST, Via alla Cascata, 38050 Povo, Trento, Italy, fax. +39 461 314 591.Google Scholar

Copyright information

© Springer-Verlag London 1998

Authors and Affiliations

  • Bruce Denby
    • 1
  • Peter Golé
    • 1
  • Jerôme Tarniewicz
    • 1
  1. 1.Université de Versailles/CETPVélizyFrance

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