Time–frequency feature representation using energy concentration: An overview of recent advances

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Cite
Sejdić, Ervin, et al. “Time–frequency Feature Representation Using Energy Concentration: An Overview of Recent Advances”. Digital Signal Processing, vol. 19, no. 1, 2009, pp. 153-8, https://doi.org/10.1016/j.dsp.2007.12.004.
Sejdić, E., Djurović, I., & Jiang, J. (2009). Time–frequency feature representation using energy concentration: An overview of recent advances. Digital Signal Processing, 19(1), 153-183. https://doi.org/10.1016/j.dsp.2007.12.004
Sejdić E, Djurović I, Jiang J. Time–frequency feature representation using energy concentration: An overview of recent advances. Digital Signal Processing. 2009;19(1):153-8.
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Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
Electric circuits
Electric networks
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
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Refrences Analysis
The category Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics 191 is the most frequently represented among the references in this article. It primarily includes studies from IEEE Transactions on Signal Processing The chart below illustrates the number of referenced publications per year.
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Citations Analysis
The first research to cite this article was titled Insight into the Fourier Transform Band Pass Filtering Technique and was published in 2008. The most recent citation comes from a 2024 study titled Insight into the Fourier Transform Band Pass Filtering Technique . This article reached its peak citation in 2023 , with 54 citations.It has been cited in 229 different journals, 20% of which are open access. Among related journals, the Sensors cited this research the most, with 17 citations. The chart below illustrates the annual citation trends for this article.
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