Entropy based detection on the time-frequency plane

A comprehensive theory for time-frequency based signal detection has been developed during the past decade. The time-frequency detectors proposed in the literature are linear structures operating on the time-frequency representation of the signals and are equivalent to quadratic receivers that are defined in the time domain. We introduce the concept of entropy based detection on the time-frequency plane. In recent years, Renyi entropy has been proposed as an effective measure for quantifying signal complexity on the time-frequency plane and some important properties of this measure have been proven. A new approach that uses the entropy functional as the test statistic for signal detection is developed. A minimum error detection algorithm is derived and the performance of this new signal detection method is demonstrated through examples.

[1]  Cédric Richard,et al.  Data-driven design and complexity control of time-frequency detectors , 1999, Signal Process..

[2]  William J. Williams,et al.  Uncertainty, information, and time-frequency distributions , 1991, Optics & Photonics.

[3]  Patrick Flandrin,et al.  A time-frequency formulation of optimum detection , 1988, IEEE Trans. Acoust. Speech Signal Process..

[4]  William J. Williams,et al.  Timefrequency Analysis of , 1995 .

[5]  Douglas L. Jones,et al.  Optimal detection using bilinear time-frequency and time-scale representations , 1995, IEEE Trans. Signal Process..

[6]  William J. Williams,et al.  Information bounds for random signals in time-frequency plane , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[7]  Olivier J. J. Michel,et al.  Measuring time-Frequency information content using the Rényi entropies , 2001, IEEE Trans. Inf. Theory.

[8]  Douglas L. Jones,et al.  Blind quadratic and time-frequency based detectors from training data , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.