Nonstationary signals information content estimation based on the local Rényi entropy in the time-frequency domain

A measure of complexity of a nonstationary multicomponent signal in the time-frequency plane can be obtained by using the Rényi entropy. If 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 of the signal. However, the Rényi entropy of one of the signal components must be known a priori. In this paper, we focus on the detection of the number of components that are present in a short time interval of the signal time-frequency distribution, using the local Rényi entropy. Results are reported on both synthetic and real data, confirming that the local Rényi entropy is a valuable tool in estimating the local number of components present in the signal.