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Proceedings Paper

Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution
Author(s): Boualem Boashash; Brian Lovell; Langford White
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Paper Abstract

Time-Frequency analysis based on the Wigner-Ville Distribution (WVD) is shown to be optimal for a class of signals where the variation of instantaneous frequency is the dominant characteristic. Spectral resolution and instantaneous frequency tracking is substantially improved by using a Modified WVD (MWVD) based on an Autoregressive spectral estimator. Enhanced signal-to-noise ratio may be achieved by using 2D windowing in the Time-Frequency domain. The WVD provides a tool for deriving descriptors of signals which highlight their FM characteristics. These descriptors may be used for pattern recognition and data clustering using the methods presented in this paper.

Paper Details

Date Published: 21 January 1988
PDF: 11 pages
Proc. SPIE 0826, Advanced Algorithms and Architectures for Signal Processing II, (21 January 1988); doi: 10.1117/12.942021
Show Author Affiliations
Boualem Boashash, University of Queensland (Australia)
Brian Lovell, University of Queensland (Australia)
Langford White, University of Queensland (Australia)


Published in SPIE Proceedings Vol. 0826:
Advanced Algorithms and Architectures for Signal Processing II
Franklin T. Luk, Editor(s)

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