A time-frequency training-based approach for robust classification of unknown transients with unknown arrival time and Doppler shift

DOI10.1016/S0016-0032(01)00029-1zbMath1010.94529OpenAlexW2004157431MaRDI QIDQ1850137

Patrick J. Loughlin, Berkant Tacer

Publication date: 2 December 2002

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0016-0032(01)00029-1

zbMATH Keywords

signal processingtransient signalsDoppler shiftambiguity functions

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Probability distributions: general theory (60E05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

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Cites Work

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• The analysis of under water vehicle non-stationary acoustic transient signals using a new fast algorithm for constructing positive time-frequency distributions
• Statistical performance of a TFD based detection scheme
• Scale and translation invariant methods for enhanced time-frequency pattern recognition
• A time-frequency formulation of optimum detection

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