Abstract

Abstract. The aim of this paper is the detailed investigation of trigonometric polynomial spaces as a tool for approximation and signal analysis. Sample spaces are generated by equidistant translates of certain de la Vallee Poussin means. The different de la Vallee Poussin means enable us to choose between better time or frequency localization. For nested sample spaces and corresponding wavelet spaces, we discuss different bases and their transformations.

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