| タイトル | Classification of Ion Mobility Data Using the Neural Network Approach |
| 本文（外部サイト） | http://hdl.handle.net/2060/20050167797 |
| 著者（英） | Duong, T. A.; Kanik, I. |
| 著者所属（英） | Jet Propulsion Lab., California Inst. of Tech. |
| 発行日 | 2005-01-01 |
| 言語 | eng |
| 内容記述 | Determination of atmospheric and surface elemental and molecular composition of various solar system bodies is essential to the development of a firm understanding of the origin and evolution of the solar system. Furthermore, such data is needed to address the intriguing question of whether or not life exists or once existed elsewhere in the Solar System. As such, these measurements are among the primary scientific goals of NASA s current and future planetary missions. In recent years, significant progress toward both miniaturization and field portability of in situ analytical separation and detection devices have been made with future planetary explorations in mind. However, despite all these advances, accurate in situ identification of atmospheric and surface compounds remains a big challenge. In response to that we are developing various hardware and software tools which would enable us to uniquely identify species of interest in a complex chemical environment. |
| NASA分類 | Lunar and Planetary Science and Exploration |
| 権利 | Copyright, Distribution under U.S. Government purpose rights |
|
