Renyi information and signal-dependent optimal kernel design

Tzu-Hsien Sang*, William J. Williams

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

70 Scopus citations


The Renyi uncertainty measure [2][4] has been proposed to be a measurement of complexity of signals. We further suggest that it can be used to evaluate the performance of different time-frequency distributions(TFDs). We provide two schemes of normalization in calculating the Renyi uncertainty measure. For the first one, TFDs are normalized by their energy, while for the second one, normalized with their volume. The behavior of the Renyi uncertainty measure under several situations is studied. A signal-dependent algorithm is developed to achieve TFDs with a minimal uncertainty measure.

Original languageEnglish
Pages (from-to)997-1000
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 1 Jan 1995
EventProceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5) - Detroit, MI, USA
Duration: 9 May 199512 May 1995

Fingerprint Dive into the research topics of 'Renyi information and signal-dependent optimal kernel design'. Together they form a unique fingerprint.

Cite this