Hand Motion Gesture Frequency Properties and Multimodal Discourse Analysis
International Journal of Computer Vision
Wavelet-based algorithm for signal analysis
EURASIP Journal on Applied Signal Processing
Null space pursuit: an operator-based approach to adaptive signal separation
IEEE Transactions on Signal Processing
On the analytic wavelet transform
IEEE Transactions on Information Theory
Time-frequency representation based on an adaptive short-time Fourier transform
IEEE Transactions on Signal Processing
Wavelet ridges for musical instrument classification
Journal of Intelligent Information Systems
Fast-varying AM-FM components extraction based on an adaptive STFT
Digital Signal Processing
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The ridges of the wavelet transform, the Gabor transform, or any time-frequency representation of a signal contain crucial information on the characteristics of the signal. Indeed, they mark the regions of the time-frequency plane where the signal concentrates most of its energy. We introduce a new algorithm to detect and identify these ridges. The procedure is based on an original form of Markov chain Monte Carlo algorithm especially adapted to the present situation. We show that this detection algorithm is especially useful for noisy signals with multiridge transforms. It is a common practice among practitioners to reconstruct a signal from the skeleton of a transform of the signal (i.e., the restriction of the transform to the ridges). After reviewing several known procedures, we introduce a new reconstruction algorithm, and we illustrate its efficiency on speech signals and its robustness and stability on chirps perturbed by synthetic noise at different SNRs