Time-frequency analysis: theory and applications
Time-frequency analysis: theory and applications
Semi-Supervised Clustering of Corner-Oriented Attributed Graphs
HIS '06 Proceedings of the Sixth International Conference on Hybrid Intelligent Systems
Multiple window spectrogram and time-frequency distributions
ICASSP '94 Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04
Multiple window time-varying spectral analysis
IEEE Transactions on Signal Processing
Iterative desensitisation of image restoration filters under wrong PSF and noise estimates
EURASIP Journal on Applied Signal Processing
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We present a method for obtaining a time-varying spectrum that is particularly suited when the data are in event-based form. This form arises in many areas of science and engineering, and especially in astronomy, where one has photon counting detectors. The method presented consists of three procedures. First, estimating the density using the kernel method; second, highpass filtering the manifestly positive density; finally, obtaining the time-frequency distribution with a modified Welch's method. For the sake of validation, event-based data are generated from a given distribution and the proposed method is used to construct the time-frequency spectrum and is compared to the original density. The results demonstrate the effectiveness of the method.