Wavelet-Based Transformations for Nonlinear Signal Processing
Nowak, Robert David
Baraniuk, Richard G.
Nonlinearities are often encountered in the analysis and processing of real-world signals. This paper develops new transformations for nonlinear signal processing. The theory of tensor norms is employed to show that wavelets provide an optimal basis for the new transformations. The results are applied to Volterra kernel identification.
DSP for Communications