Wavelets as a regularization technique for spectral density estimation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Estimation of the spectral density S(f) of a stationary random process can be viewed as a nonparametric statistical estimation problem. A nonparametric approach based on a wavelet representation for the logarithm of the unknown S(f) is introduced. This approach offers the ability to capture significant components of S(f) at different resolution levels by application of a significance test, and guarantees nonnegativity of the spectral density estimator.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages73-76
Number of pages4
ISBN (Electronic)0780308050, 9780780308053
DOIs
StatePublished - 1992
Externally publishedYes
Event1992 IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis - Victoria, Canada
Duration: Oct 4 1992Oct 6 1992

Publication series

NameProceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis

Conference

Conference1992 IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis
Country/TerritoryCanada
CityVictoria
Period10/4/9210/6/92

ASJC Scopus subject areas

  • Signal Processing

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