Mkrtchyan F.A. Problems of statistical decisions for remote environmental monitoring. In: SPIE Optics and Photonics, Earth Observing Systems XXV, 24-28 August 2020, San Diego, CA, USA , SPIE , р. 11501.
Полный текст не доступен из этого репозитория. (Заказать копию)Аннотация
Application of means of remote environmental monitoring in many cases is connected to acceptance of the statistical decision on presence on a surveyed part Terrestrial surface of this or that phenomenon. One of features of a condition of gathering of the information for such decision is the impossibility of reception the big statistical samples. Therefore development and research of optimum algorithms of distinction of the casual signals characterized by samples of limited volume, in conditions of parametrical aprioristic uncertainty are necessary. At present time there are many methods of recognition which are caused appreciably by variety of statements of concrete tasks. The feature of remote measurements is information acquisition, when the data of measurements, acquired during tracing of flying system along routes of survey, are directed to input of the processing system. As result the two dimensional image of investigated object is registered. Statistical model of spottiness for investigated space is one of models for this image. Statistical characteristics ''spottiness'' microwave temperatures can be used at recognitions and classifications of the phenomena on a surface of the ocean, distinguished by a degree of excitement. In the present work the generalized adaptive algorithm of training to acceptance of statistical decisions for exponential classes of distributions is developed at aprioristic parametrical uncertainty of conditions small samples. Numerical examples are shown. Efficiency of the developed optimum procedure for small samples is shown.
| Тип объекта: | Доклад на конференции или семинаре (Доклад) |
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| Авторы на русском. ОБЯЗАТЕЛЬНО ДЛЯ АНГЛОЯЗЫЧНЫХ ПУБЛИКАЦИЙ!: | Мкртчян Ф.А. |
| Подразделения (можно выбрать несколько, удерживая Ctrl): | 209 лаб. вычислительная |
| URI: | http://cplire.ru:8080/id/eprint/8409 |
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