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Nonparametric adaptive identification algorithms in problems of acoustic sounding of the atmosphere

The present work deals with the problem of constructing nonparametric mathematical models for interpretation of results of acoustic sounding of the atmosphere in the presence of outliers in experimental data. It is shown that the proposed adaptive nonparametric regression estimates are preferable compared to a number of the known robust parametric and nonparametric estimates. These mathematical models can also be recommended for processing of laser sensing data.