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Title:
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Time Frequency Detectors |
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Author:
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Sayeed, Akbar M.; Jones, Douglas L.
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Type:
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Conference Paper |
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Keywords:
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second-order stochastic signals; Gaussian noise; multi-channel/sensor measurements |
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Citation:
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A. M. Sayeed and D. L. Jones,"Time Frequency Detectors," in Conference on Information Sciences and Systems, |
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Abstract:
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Time-frequency representations (TFRs) provide a powerful and flexible structure for designing optimal detectors in a variety of nonstationary scenarios. In this paper, we describe a TFR-based framework for optimal detection of arbitrary second-order stochastic signals, with certain unknown or random nuisance parameters, in the presence of Gaussian noise. The framework provides a useful model for many important applications including machine fault diagnostics and radar/sonar. We emphasize a subspace-based formulation of such TFR detectors which can be exploited in a variety of ways to design new techniques. In particular, we explore an extension based on multi-channel/sensor measurements that are often available in practice to facilitate improved signal processing. In addition to potentially improved performance, the subspace-based interpretation of such multi-channel detectors provides useful information about the physical mechanisms underlying the signals of interest. |
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Date Published:
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1996-01-20 |
