Power spectral density estimation via wavelet decomposition

A. Hossen

doi:10.1049/el:20045235

Power spectral density estimation via wavelet decomposition

A. Hossen^*

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

31 Citations (Scopus)

Abstract

A soft decision algorithm for wavelet decomposition, in which a probability measure is assigned to each frequency band bearing energy, is presented. This soft decision algorithm is used as an approximate estimator of power spectral density. A staircase approximation of power spectral density (PSD) is obtained by plotting the 2^m probabilities after an m-stage decomposition. Different wavelet filters are used for estimating the PSD of a speech segment. The type of the wavelet filter used can be selected as a compromise between accuracy and complexity.

Original language	English
Pages (from-to)	1055-1056
Number of pages	2
Journal	Electronics Letters
Volume	40
Issue number	17
DOIs	https://doi.org/10.1049/el:20045235
Publication status	Published - Aug 19 2004

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1049/el:20045235

Cite this

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abstract = "A soft decision algorithm for wavelet decomposition, in which a probability measure is assigned to each frequency band bearing energy, is presented. This soft decision algorithm is used as an approximate estimator of power spectral density. A staircase approximation of power spectral density (PSD) is obtained by plotting the 2m probabilities after an m-stage decomposition. Different wavelet filters are used for estimating the PSD of a speech segment. The type of the wavelet filter used can be selected as a compromise between accuracy and complexity.",

author = "A. Hossen",

year = "2004",

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AB - A soft decision algorithm for wavelet decomposition, in which a probability measure is assigned to each frequency band bearing energy, is presented. This soft decision algorithm is used as an approximate estimator of power spectral density. A staircase approximation of power spectral density (PSD) is obtained by plotting the 2m probabilities after an m-stage decomposition. Different wavelet filters are used for estimating the PSD of a speech segment. The type of the wavelet filter used can be selected as a compromise between accuracy and complexity.

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JF - Electronics Letters

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Power spectral density estimation via wavelet decomposition

Abstract

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