Numerical Analysis of Wavelet Methods
By Albert Cohen. 2003
584 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Mathematical Physics
View Paper: https://www.semanticscholar.org/paper/c1d54e62979481354d49bbf48bd863b895c29881
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Boris N. Khoromskij
- Christoph Schwab
- Reinhold Schneider
- Wolfgang Hackbusch
- Ivan V. Oseledets
- Sergey V. Dolgov
- Heinz-Jürgen Flad
- Ronald A. DeVore
In Computer Vision and Pattern Recognition
- Zuowei Shen
- Bin Han
- Franccois Roueff
- Mohamed-Jalal Fadili
- Murad S. Taqqu
- Boris N. Khoromskij
- Eric Moulines
- Ronald A. DeVore
In Mathematical Physics
- Zuowei Shen
- Eric Moulines
- Murad S. Taqqu
- Tino Ullrich
- Patrick L. Combettes
- Stéphane Seuret
- Mohamed-Jalal Fadili
- Franccois Roueff
Citations in the corpus
- The Undecimated Wavelet Decomposition and its Reconstruction (2007, background): “Background texts on the wavelet transform include [1]–[5].”
- Sparse adaptive Taylor approximation algorithms for parametric and stochastic elliptic PDEs (2011, methodology): “We refer to [6] for a detailed treatment of wavelets.”
- A wavelet whittle estimator of the memory parameter of a nonstationary Gaussian time series (2006, methodology): “The associated scaling and wavelet functions φ and ψ satisfy (W-1)–(W-4), where α in (W-2) is a function of M which increases to infinity as M tends to infinity (see [3], Theorem 2.”
- Accelerated Projected Gradient Method for Linear Inverse Problems with Sparsity Constraints (2007, unknown): “A new generation of optimal numerical schemes has been developed for the computation of sparse solutions of differential and integral equations, exploiting adaptive and greedy strategies [12, 13, 14, 16, 17].”
- Minimax Testing of a Composite null Hypothesis Defined via a Quadratic Functional in the Model of regression (2012, methodology): “We first decompose the empirical coefficients as follows: Then, using standard arguments, we have (cid:13)(cid:13) (cid:13)(cid:13) Furthermore, by well-known properties of wavelet bases (Cohen, 2003) and the Rosenthal inequality, ).”
- On adaptive posterior concentration rates (2013, methodology): “We append the basis with boundary conditions and assume that it is associated with a R-regular multiresolution of L2, see Cohen [13] and Cohen et al. [14].”
- From Multifractal Measures to Multifractal Wavelet Series (2005, background): “For more details on unconditional characterizations of Besov spaces by wavelet coefficients (in particular when p < 1), see for instance [17, 52].”
- Spline interpolation on sparse grids (2011, background): “The following important result is due to Bourdaud [59], but see also Cohen [29] and Lemarie and Kahane [60].”
- Rate of Convergence of Space Time Approximations for Stochastic Evolution Equations (2007, background): “The proof of these inequalities and more information on wavelets can be found, e.g., in [2].”
- Optimal sup-norm rates and uniform inference on nonlinear functionals of nonparametric IV regression (2015, background): “es that keh h 0k 1= O p(J p=d): Note that Bernstein inequalities (or inverse estimates) from approximation theory imply that k@hk 1= O(Jjj=d)khk 1 for all h2 J (see Schumaker (2007) for splines and Cohen (2003) for wavelets on domains). Therefore, k@eh @h 0k 1k@ eh @( Jh 0)k 1+ k@ ( Jh 0) @ h 0k 1 O”
- Two-step regularization methods for linear inverse problems (2006, methodology): “For the exact definition and further results, like the connection to the so-called Strang-Fix conditions, we refer to [3].”