Wavelet-based decompositions for nonlinear signal processing

Robert D. Nowak; Richard G. Baraniuk

doi:10.1117/12.255237

23 October 1996 Wavelet-based decompositions for nonlinear signal processing

Robert D. Nowak, Richard G. Baraniuk

Proceedings Volume 2825, Wavelet Applications in Signal and Image Processing IV; (1996) https://doi.org/10.1117/12.255237
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

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.

Citation Download Citation

Robert D. Nowak and Richard G. Baraniuk "Wavelet-based decompositions for nonlinear signal processing", Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); https://doi.org/10.1117/12.255237

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