The DOI matches its Crossref record; 129 of the 129 references it cites were found in a registry or an index.
Time–frequency feature representation using energy concentration: An overview of recent advances
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Cites
A Wavelet Tour of Signal Processing
(1999) · Elsevier eBooks · doi:10.1016/b978-0-12-466606-1.x5000-4 · Cited by 16,227
Daubechies, I. (1992) · doi:10.1137/1.9781611970104 · Cited by 15,979
Daubechies, I., & Heil, C. (1992) · Computers in Physics · doi:10.1063/1.4823127 · Cited by 15,631
Matching pursuits with time-frequency dictionaries
Mallat, S. G., & Zhang, Z. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/78.258082 · Cited by 9,112
Statistical pattern recognition: a review
Jain, A. K., Duin, P. W., & Mao, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.824819 · Cited by 6,767
Time-frequency distributions-a review
Cohen, L. (1989) · Proceedings of the IEEE · doi:10.1109/5.30749 · Cited by 3,571
Localization of the complex spectrum: the S transform
Stockwell, R. G., Mansinha, L., & Lowe, R. P. (1996) · IEEE Transactions on Signal Processing · doi:10.1109/78.492555 · Cited by 3,486
WAVELET TRANSFORMS AND THEIR APPLICATIONS TO TURBULENCE
Farge, M. (1992) · Annual Review of Fluid Mechanics · doi:10.1146/annurev.fl.24.010192.002143 · Cited by 3,062
Foundations of Time-Frequency Analysis
Gröchenig, K. (2001) · Applied and Numerical Harmonic Analysis · doi:10.1007/978-1-4612-0003-1 · Cited by 2,923
Vetterli, M., & Kovačević, J. (1995) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 2,898
Cited by
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Brunton, S. L., & Kutz, J. N. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108380690 · Cited by 1,154
Applications of fault detection and diagnosis methods in nuclear power plants: A review
Ma, J., & Jiang, J. (2011) · Progress in Nuclear Energy · doi:10.1016/j.pnucene.2010.12.001 · Cited by 377
Self-citationRavi, D., Wong, C., Lo, B., & Yang, G.-Z. (2016) · 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN) · doi:10.1109/bsn.2016.7516235 · Cited by 269
A comparative analysis of swallowing accelerometry and sounds during saliva swallows
Dudik, J. M., Jestrović, I., Luan, B., Coyle, J. L., & Sejdić, E. (2015) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-14-3 · Cited by 72
Self-citationInfraslow oscillations in human sleep spindle activity
Lázár, Z. I., Dijk, D.-J., & Lázár, A. S. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2018.12.002 · Cited by 49
Metadata
- Authors
- Sejdić, E., Djurović, I., & Jiang, J.
- Venue
- Digital Signal Processing
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 19
- Issue
- 1
- Pages
- 153-183
- ISSN
- 1051-2004 (ISSN-L)
- OpenAlex
- W2145487065
- Cited by
- 756
- References
- 129
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- closed
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- Sejdić, E., Djurović, I., & Jiang, J. (2009). Time–frequency feature representation using energy concentration: An overview of recent advances. Digital Signal Processing. https://doi.org/10.1016/j.dsp.2007.12.004
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
