Multiresolution approximations and wavelet orthonormal bases of L^2(R)
TLDR
In this paper, the authors study the properties of multiresolution approximation and prove that it is characterized by a 2π periodic function, which is further described in terms of wavelet orthonormal bases.Abstract:
A multiresolution approximation is a sequence of embedded vector spaces V j jmember Z for approximating L 2 (R) functions. We study the properties of a multiresolution approximation and prove that it is characterized by a 2π periodic function which is further described. From any multiresolution approximation, we can derive a function ψ(x) called a wavelet such that √ 2 j ψ(2 j x −k) (k ,j)member Z 2 is an orthonormal basis of L 2 (R). This provides a new approach for understanding and computing wavelet orthonormal bases. Finally, we characterize the asymptotic decay rate of multiresolution approximation errors for functions in a Sobolev space H s .read more
Citations
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Wavelet based empirical Bayes estimation for the uniform distribution
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Some results on vanishing moments of wavelet packets, convolution and cross-correlation of wavelets
A. M. Jarrah,Nikhil Khanna +1 more
TL;DR: In this paper, the convolution and cross-correlation theorems for Hilbert transform of wavelets are proved using MRA of L 2 (R ), and some results on the vanishing moments of the scaling functions, wavelets and their convolution in two dimension are given.
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Coding of 3D medical images using 3D wavelet decompositions
TL;DR: The use of a3-D wavelet transform for the compression of 3-D medical images is investigated and the first results obtained on 3- D magnetic resonance imaging (MRI) images of a human heart are presented.
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Functional stochastic modeling and prediction of spatiotemporal processes
TL;DR: In this article, a class of nonstationary statistical models with finite-order autoregressive spatio-temporal dynamics is introduced, and the associated prediction problem is solved by implementing the Kalman filter in terms of multivariate versions of the spatial Karhunen-Loeve and wavelet transforms.
References
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TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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Decomposition of Hardy functions into square integrable wavelets of constant shape
A. Grossmann,J. Morlet +1 more
TL;DR: In this article, the authors studied square integrable coefficients of an irreducible representation of the non-unimodular $ax + b$-group and obtained explicit expressions in the case of a particular analyzing family that plays a role analogous to coherent states (Gabor wavelets) in the usual $L_2 $ -theory.
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Exact reconstruction techniques for tree-structured subband coders
TL;DR: It is shown that it is possible to design tree-structured analysis/reconstruction systems which meet the sampling rate condition and which result in exact reconstruction of the input signal.
Journal ArticleDOI
Analysis of sound patterns through wavelet transforms
TL;DR: The main features of so-called wavelet transforms are illustrated through simple mathematical examples and the first applications of the method to the recognition and visualisation of characteristic features of speech and of musical sounds are presented.