Wigner distribution decomposition and cross-term deleted representation
Signal Processing
Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Methods of System Identification for Monitoring Slowly Time-Varying Structural Systems
IIS '97 Proceedings of the 1997 IASTED International Conference on Intelligent Information Systems (IIS '97)
Time-frequency-based detection using discrete-time discrete-frequency Wigner distributions
IEEE Transactions on Signal Processing
Harmonic decomposition of audio signals with matching pursuit
IEEE Transactions on Signal Processing
Improving the readability of time-frequency and time-scalerepresentations by the reassignment method
IEEE Transactions on Signal Processing
Spectrogram segmentation by means of statistical features for non-stationary signal interpretation
IEEE Transactions on Signal Processing
Optimizing time-frequency kernels for classification
IEEE Transactions on Signal Processing
Matching pursuits with a wave-based dictionary
IEEE Transactions on Signal Processing
A four-parameter atomic decomposition of chirplets
IEEE Transactions on Signal Processing
Environmental sound recognition with time-frequency audio features
IEEE Transactions on Audio, Speech, and Language Processing
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We propose methodologies to automatically classify time-varying warning signals from an acoustic monitoring system that indicate the potential catastrophic structural failures of reinforced concrete structures. Since missing even a single warning signal may prove costly, it is imperative to develop a classifier with high probability of correctly classifying the warning signals. Due to the time-varying nature of these signals, various time-frequency classifiers are considered. We propose a new time-frequency decomposition-based classifier using the modified matching pursuit algorithm for an actual acoustic monitoring system. We investigate the superior performance of the classifier and compare it with existing classifiers for various sets of acoustic emissions, including warning signals from real-world faulty structures. Furthermore, we study the performance of the new classifier under different test conditions.