Multiple window time-frequency and time-scale analysis

Metin Bayram; Richard G. Baraniuk

doi:10.1117/12.255431

Multiple window time-frequency and time-scale analysis

Metin Bayram, Richard G. Baraniuk

Research output: Contribution to journal › Conference article

3 Scopus citations

Abstract

We propose an extension of Thomson's multiple window spectrum estimation for stationary random processes to the time-varying spectrum estimation of non-stationary random processes. Unlike previous extensions of Thomson's method, in this paper we identify and utilize optimally concentrated window and wavelet functions for the timefrequency and time-scale planes respectively. Moreover, we develop a statistical test for detecting and extracting chirping line components.

Original language	English (US)
Pages (from-to)	174-185
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	2846
DOIs	https://doi.org/10.1117/12.255431
State	Published - Oct 22 1996
Event	Advanced Signal Processing Algorithms, Architectures, and Implementations VI 1996 - Denver, United States Duration: Aug 4 1996 → Aug 9 1996

Keywords

Multiple window method
Non-stationary processes
Spectrum estimation

ASJC Scopus subject areas

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

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title = "Multiple window time-frequency and time-scale analysis",

abstract = "We propose an extension of Thomson's multiple window spectrum estimation for stationary random processes to the time-varying spectrum estimation of non-stationary random processes. Unlike previous extensions of Thomson's method, in this paper we identify and utilize optimally concentrated window and wavelet functions for the timefrequency and time-scale planes respectively. Moreover, we develop a statistical test for detecting and extracting chirping line components.",

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AU - Bayram, Metin

AU - Baraniuk, Richard G.

PY - 1996/10/22

Y1 - 1996/10/22

N2 - We propose an extension of Thomson's multiple window spectrum estimation for stationary random processes to the time-varying spectrum estimation of non-stationary random processes. Unlike previous extensions of Thomson's method, in this paper we identify and utilize optimally concentrated window and wavelet functions for the timefrequency and time-scale planes respectively. Moreover, we develop a statistical test for detecting and extracting chirping line components.

AB - We propose an extension of Thomson's multiple window spectrum estimation for stationary random processes to the time-varying spectrum estimation of non-stationary random processes. Unlike previous extensions of Thomson's method, in this paper we identify and utilize optimally concentrated window and wavelet functions for the timefrequency and time-scale planes respectively. Moreover, we develop a statistical test for detecting and extracting chirping line components.

KW - Multiple window method

KW - Non-stationary processes

KW - Spectrum estimation

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DO - 10.1117/12.255431

M3 - Conference article

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

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

SN - 0277-786X

T2 - Advanced Signal Processing Algorithms, Architectures, and Implementations VI 1996

Y2 - 4 August 1996 through 9 August 1996

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