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Title:
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Time-frequency analysis and pattern recognition using singular value decomposition of the Wigner-Ville distribution |
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Author:
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Boashash, B; Lovell, B; White, L.B.
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Abstract:
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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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Description:
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This paper presents a modified Wigner-Ville Distribution (MWVD) using Auto-regressive spectral analysis to improve the spectral resolution; it also presents descriptors which highlight a signal's FM characteristics and a data clustering algorithm for classification.
(Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354).
In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). |
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URI:
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http://hdl.handle.net/10576/10829
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Date:
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1987 |