Title :
Wavelet-based transformations for nonlinear signal processing
Author :
Nowak, Robert D. ; Baraniuk, Richard G.
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
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
Keywords :
Volterra series; filtering theory; signal processing; tensors; wavelet transforms; Volterra filter; Volterra kernel identification; nonlinear signal processing; nonlinearities; signal analysis; tensor norms; wavelet based transformations; Couplings; Filtering; Harmonic distortion; Kernel; Machinery; Signal analysis; Signal processing; Speech processing; Tensile stress; Wavelet domain;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.599534
