Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution

Boualem Boashash; Brian Lovell; Langford White

doi:10.1117/12.942021

21 January 1988 Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution

Boualem Boashash, Brian Lovell, Langford White

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Proceedings Volume 0826, Advanced Algorithms and Architectures for Signal Processing II; (1988) https://doi.org/10.1117/12.942021
Event: 31st Annual Technical Symposium on Optical and Optoelectronic Applied Sciences and Engineering, 1987, San Diego, CA, United States

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.

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Boualem Boashash, Brian Lovell, and Langford White "Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution", Proc. SPIE 0826, Advanced Algorithms and Architectures for Signal Processing II, (21 January 1988); https://doi.org/10.1117/12.942021

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