Wavelet-based decompositions for nonlinear signal processing

Robert D. Nowak; Richard G. Baraniuk

doi:10.1117/12.255237

Wavelet-based decompositions for nonlinear signal processing

Robert D. Nowak, Richard G. Baraniuk

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Pages	260-271
Number of pages	12
Volume	2825
DOIs	https://doi.org/10.1117/12.255237
State	Published - 1996
Event	Wavelet Applications in Signal and Image Processing IV - Denver, CO, United States Duration: Aug 6 1996 → Aug 6 1996

Other

Other	Wavelet Applications in Signal and Image Processing IV
Country/Territory	United States
City	Denver, CO
Period	8/6/96 → 8/6/96

Keywords

nonlinear signal processing
tensor spaces
wavelets

ASJC Scopus subject areas

Applied Mathematics
Computer Science Applications
Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials
Condensed Matter Physics

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10.1117/12.255237

Cite this

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title = "Wavelet-based decompositions for nonlinear signal processing",

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.",

keywords = "nonlinear signal processing, tensor spaces, wavelets",

author = "Nowak, {Robert D.} and Baraniuk, {Richard G.}",

year = "1996",

doi = "10.1117/12.255237",

language = "English (US)",

volume = "2825",

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note = "Wavelet Applications in Signal and Image Processing IV ; Conference date: 06-08-1996 Through 06-08-1996",

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T1 - Wavelet-based decompositions for nonlinear signal processing

AU - Nowak, Robert D.

AU - Baraniuk, Richard G.

PY - 1996

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N2 - 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.

AB - 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.

KW - nonlinear signal processing

KW - tensor spaces

KW - wavelets

UR - http://www.scopus.com/inward/record.url?scp=78751637405&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78751637405&partnerID=8YFLogxK

U2 - 10.1117/12.255237

DO - 10.1117/12.255237

M3 - Conference contribution

AN - SCOPUS:78751637405

VL - 2825

SP - 260

EP - 271

BT - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Wavelet Applications in Signal and Image Processing IV

Y2 - 6 August 1996 through 6 August 1996

ER -

Wavelet-based decompositions for nonlinear signal processing

Abstract

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Keywords

ASJC Scopus subject areas

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