Piotr Kulczycki Kernel Estimators in Industrial Applications w: „Soft Computing Applications in Industry” B. Prasad (ed.), Springer-Verlag, Berlin (Niemcy), 2008, ss. 69-91.

Abstract:
In this chapter the concept of statistical kernel estimators is considered. Thanks to the possibilities and availability of modern computer systems, these are becoming the basic method of nonparametric estimation, allowing characteristics of random variables to be calculated without arbitrary assumptions concerning the membership of their distribution to a fixed class. As a consequence, new procedures in the area of advanced information technology can be developed - up to now unobtainable by classical methods - with the additional ability to apply modern artificial intelligence algorithms to these ends. In this chapter the basics of kernel estimators methodology are described, followed by their applicational possibilities in example problems of contemporary industrial challenges.

Keywords:
soft computing, nonparametric estimation, kernel estimators, information technology, data analysis and exploration, industrial applications, fault detection, mobile phone, parametric identification, optimal control, wireless teletransmission system.