A Novel Pseudo-Bayesian Approach for Robust Multi-Ridge Detection and Mode Retrieval
Abstract
This paper introduces a novel approach for extracting the elementary components present in an observed nonstationary mixture signal. Our technique based on a pseudo-Bayesian approach operates in the time-frequency plane and sequentially estimates the ridge of each component that is required for mode extraction. We compare our results with those obtained with the state-of-the-art Brevdo method which has shown its efficiency for disentangling multicomponent noisy signals. Our results reveal an improvement of the reconstruction performance when compared to the state of the art.
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