摘要
A scheme that utilizes satellite radiobrightness to infer surface parameters without losing the nonlinearity between the measured quantities and desired variables is examined. The approach is to incorporate products from the 1-dimensional hydrology/radiobrightness (1dH/R) model into the dynamic learning neural network (DLNN) manages the nonlinear mappings.
原文 | ???core.languages.en_GB??? |
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頁面 | 1096-1098 |
頁數 | 3 |
出版狀態 | 已出版 - 1997 |
事件 | Proceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 3 (of 4) - Singapore, Singapore 持續時間: 3 8月 1997 → 8 8月 1997 |
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???event.eventtypes.event.conference??? | Proceedings of the 1997 IEEE International Geoscience and Remote Sensing Symposium, IGARSS'97. Part 3 (of 4) |
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城市 | Singapore, Singapore |
期間 | 3/08/97 → 8/08/97 |