23 October 1996 Wavelet-based decompositions for nonlinear signal processing
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Abstract
Nonlinearities are often encountered in the analysis and processing of real-world signals. This paper develops new signal decompositions for nonlinear analysis and processing. The theory of tensor norms is employed to show that wavelets provide an optimal basis for the nonlinear signal decompositions. The nonlinear signal decompositions are also applied to signal processing problems.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert D. Nowak, Richard G. Baraniuk, "Wavelet-based decompositions for nonlinear signal processing", Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255237; https://doi.org/10.1117/12.255237
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KEYWORDS
Nonlinear optics

Wavelets

Signal processing

Nonlinear filtering

Electronic filtering

Linear filtering

Filtering (signal processing)

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