scholarly journals Inference on fractal processes using multiresolution approximation

Biometrika ◽  
2007 ◽  
Vol 94 (2) ◽  
pp. 313-334 ◽  
Author(s):  
K. Falconer ◽  
C. Fernandez
Keyword(s):  
Multiresolution Approximation

Normal Multiresolution Approximation of Curves

2004 ◽  
Vol 20 (3) ◽  
pp. 399-463 ◽  
Author(s):  
Olof Runborg ◽  
Wim Sweldens ◽  
Ingrid Daubechies
Keyword(s):  
Multiresolution Approximation

scholarly journals Quasi-Positive Delta Sequences and Their Applications in Wavelet Approximation

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Shyam Lal ◽  
Susheel Kumar
Keyword(s):  
Wavelet Analysis ◽  
Supremum Norm ◽  
Wavelet Estimator ◽  
Wavelet Approximation ◽  
Wavelet Expansions ◽  
Multiresolution Approximation ◽  
First Time ◽  
Approximation Of A Function

A sufficient literature is available for the wavelet error of approximation of certain functions in theL2-norm. There is no work in context of multiresolution approximation of a function in the sense of sup-error. In this paper, for the first time, wavelet estimator for the approximation of a functionfbelonging toLipα[a,b]class under supremum norm has been obtained. Working in this direction, four new theorems on the wavelet approximation of a functionfbelonging toLipα,0<α≤1class using the projectionPmfof its wavelet expansions have been estimated. The calculated estimator is best possible in wavelet analysis.

scholarly journals Multiresolution Approximation of Polyhedral Solids

1997 ◽  
pp. 327-343
Author(s):  
D. Ayala ◽  
P. Brunet ◽  
R. Joan-Arinyo ◽  
I. Navazo
Keyword(s):  
Multiresolution Approximation

Surface-Tracing-Based LASAR 3-D Imaging Method via Multiresolution Approximation

2008 ◽  
Vol 46 (11) ◽  
pp. 3719-3730 ◽  
Author(s):  
Shi Jun ◽  
Zhang Xiaoling ◽  
Jianyu Yang ◽  
Wang Yinbo
Keyword(s):  
Imaging Method ◽  
Multiresolution Approximation

A Multiresolution Approximation Theory of Fractal Transform

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 173-186
Author(s):  
Bing Cheng ◽  
Xiaokun Zhu
Keyword(s):  
Approximation Theory ◽  
Time Domain ◽  
Theoretical Basis ◽  
Model Complexity ◽  
Data Complexity ◽  
Image Encoding ◽  
Single Time ◽  
Multiresolution Approximation ◽  
Signal Image

In this paper, we show that the fractal transform (FT) constitutes a multiresolution approximation to the square-integrable space L2(Td) for d≥1, where T is the interval (-∞,∞). This provides a theoretical basis for the successful applications of the fractal transform algorithms in signal/image encoding. There are many similarities between fractal-based and wavelet-based approximations. However, they are undamentally different from each other in many aspects. Fractal-based multiresolution approximation to signals/images is by a way of self-increasing model complexity, and wavelet-based multiresolution approximation to signals/images is by a way of decomposing data complexity into single (time domain) components.

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