Convex Optimization approach to signals with fast varying instantaneous frequency

Abstract : Motivated by the limitation of analyzing oscillatory signals composed of multiple components with fast-varying instantaneous frequency, we approach the time-frequency analysis problem by optimization. Based on the proposed adaptive harmonic model, the time-frequency representation of a signal is obtained by directly minimizing a functional, which involves few properties an "ideal time-frequency representation" should satisfy, for example, the signal reconstruction and concentrative time frequency representation. FISTA (Fast Iterative Shrinkage-Thresholding Algorithm) is applied to achieve an efficient numerical approximation of the functional. We coin the algorithm as {\it Time-frequency bY COnvex OptimizatioN} (Tycoon). The numerical results confirm the potential of the Tycoon algorithm.
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Applied and Computational Harmonic Analysis, Elsevier, 2018, 44 (1), pp.89 - 122. 〈10.1016/j.acha.2016.03.008〉
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Matthieu Kowalski, Adrien Meynard, Hau-Tieng Wu. Convex Optimization approach to signals with fast varying instantaneous frequency. Applied and Computational Harmonic Analysis, Elsevier, 2018, 44 (1), pp.89 - 122. 〈10.1016/j.acha.2016.03.008〉. 〈hal-01199615v2〉

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