This book explains the nature and computation of mathematical wavelets, which provide a framework and methods for the analysis and the synthesis of signals, images, and other arrays of data. The material presented here addresses the au­ dience of engineers, financiers, scientists, and students looking for explanations of wavelets at the undergraduate level. It requires only a working knowledge or memories of a first course in linear algebra and calculus. The first part of the book answers the following two questions: What are wavelets? Wavelets extend Fourier analysis. How are wavelets computed? Fast transforms compute them. To show the practical significance of wavelets, the book also provides transitions into several applications: analysis (detection of crashes, edges, or other events), compression (reduction of storage), smoothing (attenuation of noise), and syn­ thesis (reconstruction after compression or other modification). Such applications include one-dimensional signals (sounds or other time-series), two-dimensional arrays (pictures or maps), and three-dimensional data (spatial diffusion). The ap­ plications demonstrated here do not constitute recipes for real implementations, but aim only at clarifying and strengthening the understanding of the mathematics of wavelets.

A Algorithms for Wavelet Transforms.- 1 Haar's Simple Wavelets.- 2 Multidimensional Wavelets and Applications.- 3 Algorithms for Daubechies Wavelets.- B Basic Fourier Analysis.- 4 Inner Products and Orthogonal Projections.- 5 Discrete and Fast Fourier Transforms.- 6 Fourier Series for Periodic Functions.- C Computation and Design of Wavelets.- 7 Fourier Transforms on the Line and in Space.- 8 Daubechies Wavelets Design.- 9 Signal Representations with Wavelets.- D Directories.- Acknowledgments.- Collection of Symbols.