Locally Optimized Adaptive Directional Time–Frequency Distributions
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Signal Processing
Link
http://link.springer.com/article/10.1007/s00034-018-0802-z/fulltext.html
Reference46 articles.
1. S. Ali, N.A. Khan, M. Haneef, X. Luo, Blind source separation schemes for mono-sensor and multi-sensor systems with application to signal detection. Circuits Syst. Signal Process. 36(11), 4615–4636 (2017). https://doi.org/10.1007/s00034-017-0533-6
2. M.G. Amin, B. Jokanovic, Y.D. Zhang, F. Ahmad, A sparsity-perspective to quadratic time–frequency distributions. Digit. Signal Process. 46, 175–190 (2015). https://doi.org/10.1016/j.dsp.2015.06.011
3. F. Auger, P. Flandrin, Improving the readability of time–frequency and time-scale representations by the reassignment method. IEEE Trans. Signal Process. 43(5), 1068–1089 (1995). https://doi.org/10.1109/78.382394
4. M.A. Awal, B. Boashash, An automatic fast optimization of quadratic time-frequency distribution using the hybrid genetic algorithm. Signal Process. 131, 134–142 (2017). https://doi.org/10.1016/j.sigpro.2016.08.017
5. M.A. Awal, S. Ouelha, S. Dong, B. Boashash, A robust high-resolution time–frequency representation based on the local optimization of the short-time fractional Fourier transform. Digit. Signal Process. 70(Supplement C), 125–144 (2017). https://doi.org/10.1016/j.dsp.2017.07.022
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