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- W3081219982 abstract "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." @default.
- W3081219982 created "2020-09-01" @default.
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- W3081219982 date "2020-08-20" @default.
- W3081219982 modified "2023-09-23" @default.
- W3081219982 title "Problems of statistical decisions for remote environmental monitoring" @default.
- W3081219982 doi "https://doi.org/10.1117/12.2567514" @default.
- W3081219982 hasPublicationYear "2020" @default.
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