Wavelets, Approximation, and Statistical Applications
β Scribed by Wolfgang HΓ€rdle, Gerard Kerkyacharian, Dominique Picard, Alexander Tsybakov
- Publisher
- Springer
- Year
- 2000
- Tongue
- English
- Leaves
- 284
- Series
- Lecture Notes in Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
<p>The mathematical theory of ondelettes (wavelets) was developed by Yves Meyer and many collaborators about 10 years ago. It was designed for apΒ proximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, image and signal processΒ
FROM THE PUBLISHERThe mathematical theory of wavelets was developed by Yves Meyer and many collaborators about ten years ago. It was designed for approximation of possibly irregular functions and surfaces and was successfully applied in data compression, turbulence analysis, and image and signal pro
<p><em>Approximation Theory, Wavelets and Applications</em> draws together the latest developments in the subject, provides directions for future research, and paves the way for collaborative research. The main topics covered include constructive multivariate approximation, theory of splines, spline
<p><em>Approximation Theory, Wavelets and Applications</em> draws together the latest developments in the subject, provides directions for future research, and paves the way for collaborative research. The main topics covered include constructive multivariate approximation, theory of splines, spline
<p>This book presents the basic concepts of functional analysis, wavelet analysis and thresholding. It begins with an elementary chapter on preliminaries such as basic concepts of functional analysis, a brief tour of the wavelet transform, Haar scaling functions and function space, wavelets, symlets