Wavelets provide new capabilities for analyzing real-time signals. This introductory article provides an overview and presents the basic mechanisms involved in wavelets. In many signal processing ...

In a series of recent articles on nonparametric regression, Donoho and Johnstone developed wavelet-shrinkage methods for recovering unknown piecewise-smooth deterministic signals from noisy data.

In this paper we discuss how to use wavelet decompositions to select a regression model. The methodology relies on a minimum description length criterion which is used to determine the number of ...

Professor Ingrid Daubechies’ groundbreaking work on wavelet theory has transformed the numerical treatment of images and signal processing, providing standard and flexible algorithms for data ...

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