Non-Stationary Signal Classification Using Joint Frequency Analysis

Time-varying short-term spectral estimates have been successfully applied in many classification tasks. However, they are still insufficient for many non-stationary signals where time-varying information is useful. In this paper, we propose to improve the deficiencies of current short-term feature a...

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Main Authors: Sukittanon, Somsak, Atlas, Les E, Pitton, James W, McLaughlin, Jack
Format: Report
Language:English
Subjects:
CLASSIFICATION
ESTIMATES
FEATURE EXTRACTION
FREQUENCY ANALYSIS
FREQUENCY ANALYZERS
FREQUENCY MODULATION
Miscellaneous Detection and Detectors
Radio Communications
Radiofrequency Wave Propagation
SIGNAL CLASSIFICATION
SIGNAL PROCESSING
SPECTRA
TIME
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Atlas, Les E
Pitton, James W
McLaughlin, Jack
description Time-varying short-term spectral estimates have been successfully applied in many classification tasks. However, they are still insufficient for many non-stationary signals where time-varying information is useful. In this paper, we propose to improve the deficiencies of current short-term feature analysis by adding information to describe the time-varying behavior of the signals. Our proposed method, which is motivated by the human auditory system, can be applied to several non-stationary signal types. Real world communication signals were used for experimental verification. These experimental results, assessed with a conventional probabilistic classifier, showed significant improvement when the new features were added to short-term spectral estimates. Sponsored in part by the Air Force Research Laboratory (AFRL).
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source DTIC Technical Reports
subjects CLASSIFICATION
ESTIMATES
FEATURE EXTRACTION
FREQUENCY ANALYSIS
FREQUENCY ANALYZERS
FREQUENCY MODULATION
Miscellaneous Detection and Detectors
Radio Communications
Radiofrequency Wave Propagation
SIGNAL CLASSIFICATION
SIGNAL PROCESSING
SPECTRA
TIME
title Non-Stationary Signal Classification Using Joint Frequency Analysis
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