Abstract
Most of the common techniques for estimating conditional probability densities are inappropriate for applications involving periodic variables. In this paper we apply two novel techniques to the problem of extracting the distribution of wind vector directions from radar catterometer data gathered by a remote-sensing satellite.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the International Conference on Artificial Neural Networks (ICANN'95) |
| Editors | F. Fougelman-Soulie, P. Gallinari |
| Publisher | EC2 et Cie |
| Pages | 209-214 |
| Number of pages | 6 |
| Volume | 2 |
| ISBN (Print) | 9782910085193, 2910085198 |
| Publication status | Published - 1995 |
Bibliographical note
International Conference on Artificial Neural Networks, Paris (FR), October 2005.Keywords
- estimating conditional probability densities, periodic variables, distribution of wind vector directions, radar scatterometer data, remote-sensing satellite