Name
Title | ||
|---|---|---|
Combining signal processing and machine learning techniques for real time measurement of raindrops |
Abstract | ||
|---|---|---|
The data acquisition system for a new type of optical disdrometer is presented. As the device must measure sizes and velocities of raindrops as small as 0.1 mm diameter in real time in the presence of high noise and a variable baseline, algorithm design has been a challenge. The combining of standard signal processing techniques and machine learning methods (in this case, a neural network) has been essential to obtaining good performance |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/19.982973 | Instrumentation and Measurement, IEEE Transactions |
Keywords | Field | DocType |
data acquisition,geophysical signal processing,learning (artificial intelligence),meteorological instruments,meteorology,multilayer perceptrons,rain,data acquisition system,dual beam disdrometer,high noise,machine learning methods,meteorology,multilayer perceptions,optical disdrometer,photodiode current variations,power spectral density,raindrop sizes,raindrop velocities,real time instrumentation,real time raindrop measurement,signal processing techniques,slope algorithm,variable baseline | Signal processing,Algorithm design,Computer science,Data acquisition,Electronic engineering,Artificial intelligence,Disdrometer,Artificial neural network,Drop (liquid),Geophysical signal processing,Machine learning | Journal |
Volume | Issue | ISSN |
50 | 6 | 0018-9456 |
Citations | PageRank | References |
1 | 0.47 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| B. Denby | 1 | 268 | 26.69 |
| Jean-christophe Prévotet | 2 | 38 | 12.43 |
| Patrick Garda | 3 | 60 | 20.26 |
| Bertrand Granado | 4 | 88 | 21.68 |
| Laurent Barthes | 5 | 1 | 0.47 |
| Peter Golé | 6 | 1 | 0.81 |
| Jacques Lavergnat | 7 | 2 | 1.40 |
| Jean-Yves Delahaye | 8 | 1 | 0.47 |