The time-frequency Rényi entropy provides a measure of complexity of a nonstationary multicomponent signal in the time-frequency plane. When the complexity of a signal corresponds to the number of its components, then this information is measured as the Rényi entropy of the time-frequency distribution (TFD) of the signal. This article presents a solution to the problem of detecting the number of components that are present in short-time interval of the signal TFD, using the short-term Rényi entropy. The method is automatic and it does not require a prior information about the signal. The algorithm is applied on both synthetic and real data, using a quadratic separable kernel TFD. The results confirm that the short-term Rényi entropy can be an effective tool for estimating the local number of components present in the signal. The key aspect of selecting a suitable TFD is also discussed.
CITATION STYLE
Boashash, B., & Saulig, N. (2011). Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy. Eurasip Journal on Advances in Signal Processing, 2011. https://doi.org/10.1186/1687-6180-2011-125
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