Problems of Statistical Decisions in Ocean Monitoring

Application of means of geoinformation 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. 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.