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Measuring time-frequency information content using the Renyi entropies
Open accessAbstract
The generalized entropies of Renyi inspire new measures for estimating signal information and complexity in the time-frequency plane. When applied to a time-frequency representation (TFR) from Cohen's class or the affine class, the Renyi entropies conform closely to the notion of complexity that we use when visually inspecting time-frequency images. These measures possess several additional interesting and useful properties, such as accounting and cross-component and transformation invariances, that make them natural for time-frequency analysis. This paper comprises a detailed study of the properties and several potential applications of the Renyi entropies, with emphasis on the mathematical foundations for quadratic TFRs. In particular, for the Wigner distribution, we establish that there exist signals for which the measures are not well defined.
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Singleton, R. K., Strangas, E. G., & Aviyente, S. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2336616 · Cited by 364
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Kountouris, M., & Pappas, N. (2021) · IEEE Communications Magazine · doi:10.1109/mcom.001.2000604 · Cited by 334
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Flandrin, P., & Borgnat, P. (2010) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2044839 · Cited by 264
Self-citationWavelets and functional magnetic resonance imaging of the human brain
Bullmore, E., Fadili, J., Maxim, V., Şendur, L., Whitcher, B., Suckling, J., Brammer, & Breakspear, M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.012 · Cited by 261
Metadata
- Authors
- Baraniuk, R. G., Flandrin, P., Janssen, A. J. E. M., & Michel, O. J. J.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2001-05
- Volume
- 47
- Issue
- 4
- Pages
- 1391-1409
- ISSN
- 0018-9448 (ISSN-L)
- OpenAlex
- W2100620757
- Cited by
- 493
- References
- 33
- FWCI
- 16.15
- Type
- journal article
- Language
- en
- Open access
- green
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