Window design for signal-dependent spectrogram using optimal kernel techniques

Chad C. Carson; Richard G. Baraniuk

doi:10.1117/12.255443

Window design for signal-dependent spectrogram using optimal kernel techniques

Chad C. Carson, Richard G. Baraniuk

Houston Methodist

Research output: Contribution to journal › Conference article › peer-review

Abstract

Time-frequency distributions (TFDs) have proven useful in a wide variety of nonstationary signal processing applications. While sophisticated optimal bilinear TFDs have been developed to extract the maximum possible timefrequency information from signals, certain applications dictate simpler linear, running-FFT processing techniques. In this paper, we propose a signal-dependent short-time Fourier transform/spectrogram that enjoys many of the advantages of optimal bilinear TFDs yet retains the simplicity and efficiency of running-FFT processing. In addition, we extend the optimal kernel design problem to linear spaces of signals.

Original language	English (US)
Pages (from-to)	296-305
Number of pages	10
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	2846
DOIs	https://doi.org/10.1117/12.255443
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

Optimal kernel design
Spectrogram
Time-frequency analysis
Wigner distribution

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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10.1117/12.255443

Cite this

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title = "Window design for signal-dependent spectrogram using optimal kernel techniques",

abstract = "Time-frequency distributions (TFDs) have proven useful in a wide variety of nonstationary signal processing applications. While sophisticated optimal bilinear TFDs have been developed to extract the maximum possible timefrequency information from signals, certain applications dictate simpler linear, running-FFT processing techniques. In this paper, we propose a signal-dependent short-time Fourier transform/spectrogram that enjoys many of the advantages of optimal bilinear TFDs yet retains the simplicity and efficiency of running-FFT processing. In addition, we extend the optimal kernel design problem to linear spaces of signals.",

keywords = "Optimal kernel design, Spectrogram, Time-frequency analysis, Wigner distribution",

author = "Carson, \{Chad C.\} and Baraniuk, \{Richard G.\}",

note = "Funding Information: *This work was supported by the National Science Foundation, grant no. MIP—9457438, and the Office of Naval Research, grant no. N00014—95—1—0849. Email: carson{\textcopyright}cs.berkeley.edu, richb{\textcopyright}rice.edu; URL: http://www-dsp.rice.edu. Publisher Copyright: {\textcopyright} 1996 SPIE. All rights reserved.; Advanced Signal Processing Algorithms, Architectures, and Implementations VI 1996 ; Conference date: 04-08-1996 Through 09-08-1996",

year = "1996",

month = oct,

day = "22",

doi = "10.1117/12.255443",

language = "English (US)",

volume = "2846",

pages = "296--305",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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TY - JOUR

T1 - Window design for signal-dependent spectrogram using optimal kernel techniques

AU - Carson, Chad C.

AU - Baraniuk, Richard G.

N1 - Funding Information: *This work was supported by the National Science Foundation, grant no. MIP—9457438, and the Office of Naval Research, grant no. N00014—95—1—0849. Email: carson©cs.berkeley.edu, richb©rice.edu; URL: http://www-dsp.rice.edu. Publisher Copyright: © 1996 SPIE. All rights reserved.

PY - 1996/10/22

Y1 - 1996/10/22

N2 - Time-frequency distributions (TFDs) have proven useful in a wide variety of nonstationary signal processing applications. While sophisticated optimal bilinear TFDs have been developed to extract the maximum possible timefrequency information from signals, certain applications dictate simpler linear, running-FFT processing techniques. In this paper, we propose a signal-dependent short-time Fourier transform/spectrogram that enjoys many of the advantages of optimal bilinear TFDs yet retains the simplicity and efficiency of running-FFT processing. In addition, we extend the optimal kernel design problem to linear spaces of signals.

AB - Time-frequency distributions (TFDs) have proven useful in a wide variety of nonstationary signal processing applications. While sophisticated optimal bilinear TFDs have been developed to extract the maximum possible timefrequency information from signals, certain applications dictate simpler linear, running-FFT processing techniques. In this paper, we propose a signal-dependent short-time Fourier transform/spectrogram that enjoys many of the advantages of optimal bilinear TFDs yet retains the simplicity and efficiency of running-FFT processing. In addition, we extend the optimal kernel design problem to linear spaces of signals.

KW - Optimal kernel design

KW - Spectrogram

KW - Time-frequency analysis

KW - Wigner distribution

UR - https://www.scopus.com/pages/publications/85076735630

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U2 - 10.1117/12.255443

DO - 10.1117/12.255443

M3 - Conference article

AN - SCOPUS:85076735630

SN - 0277-786X

VL - 2846

SP - 296

EP - 305

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

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

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

Y2 - 4 August 1996 through 9 August 1996

ER -

Window design for signal-dependent spectrogram using optimal kernel techniques

Abstract

Keywords

ASJC Scopus subject areas

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