| タイトル | Feature combinations and the divergence criterion |
| 本文（外部サイト） | http://hdl.handle.net/2060/19770007852 |
| 著者（英） | Decell, H. P., Jr.; Mayekar, S. M. |
| 著者所属（英） | Houston Univ. |
| 発行日 | 1976-06-01 |
| 言語 | eng |
| 内容記述 | Classifying large quantities of multidimensional remotely sensed agricultural data requires efficient and effective classification techniques and the construction of certain transformations of a dimension reducing, information preserving nature. The construction of transformations that minimally degrade information (i.e., class separability) is described. Linear dimension reducing transformations for multivariate normal populations are presented. Information content is measured by divergence. |
| NASA分類 | NUMERICAL ANALYSIS |
| レポートNO | 77N14795
REPT-56
NASA-CR-151131 |
| 権利 | No Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/183597 |
