Various methods for estimation of unknown functions from the set of noisy measurements are applicable to a wide variety of problems. Among them the non-parametric algorithms based on the parzenkernel are commonly use...
详细信息
ISBN:
(纸本)9789819916382;9789819916399
Various methods for estimation of unknown functions from the set of noisy measurements are applicable to a wide variety of problems. Among them the non-parametric algorithms based on the parzenkernel are commonly used. Our method is basically developed for multidimensional case. The two-dimensional version of the method is thoroughly explained and analysed. The proposed algorithm is an effective and efficient solution significantly improving computational speed. Computational complexity and speed of convergence of the algorithm are also studied. Some applications for solving real problems with our algorithms are presented. Our approach is applicable to multidimensional regression function estimation as well as to estimation of derivatives of functions. It is worth noticing that the presented algorithms have already been used successfully in various image processing applications, achieving significant accelerations of calculations.
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