Paper
13 November 2003 Design-adapted wavelet estimator for two-dimensional tensor product irregular designs
Véronique A Delouille, Jo Simoens, Rainer von Sachs
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Abstract
We treat nonparametric estimation of a regression function defined on a 'tensor product irregular grid,' that is, a grid constructed as the Cartesian product of two irregular one-dimensional grids. Our wavelet-type estimator is based on a wavelet transform which is the tensor product of two one-dimensional design-adapted wavelet transforms. We propose a denoising scheme and show the performance of the resulting estimator through a simulation study.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Véronique A Delouille, Jo Simoens, and Rainer von Sachs "Design-adapted wavelet estimator for two-dimensional tensor product irregular designs", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); https://doi.org/10.1117/12.505662
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Wavelets

Wavelet transforms

Matrices

Signal to noise ratio

Biological research

Denoising

Product engineering

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