The paper presents an innovation of the amplitude quantization method to process measured signals. The method allows to quantify a signal using lower number of quantization levels with low quantization noise in the investigated area. Such quantization makes possible considerable data compression in real time without complicated compression algorithms. The quantization was designed for easy automatic processing of long signal segments. and Článek představuje inovaci metody výškového kvantování měřených signálů. Tato metoda umožňuje kvantovat signál na výrazně menší počet kvantovacích hladin, a to s malým kvantovacím šumem ve zkoumané oblasti. Kvantování tak umožňuje výraznou kompresi dat přímo v reálném čase bez složitých kompresních algoritmů. Bylo speciálně navrženo pro snadné a rychlé automatické zpracování dlouhých úseků signálů.
The paper presents new methodology how to find and estimate the main features of time series to achieve the reduction of their components (dimensionality reduction) and so to provide the compression of information contained in it under keeping the selected features invariant. The presented compression algorithm is based on estimation of truncated time series components in such a way that the spectrum functions of both original and truncated time series are sufficiently close together. In the end, the set of examples is shown to demonstrate the algorithm performance and to indicate the applications of the presented methodology.