23 May 2014 Sparse reconstruction of multi-window time-frequency representation based on Hermite functions
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Abstract
Multi-window spectrograms offer higher energy concentration in contrast to the traditional single-window spec- trograms. However, these quadratic time-frequency distributions were not introduced to deal with randomly undersampled signals. This paper applies sparse reconstruction techniques to provide time-frequency represen- tations of nonstationary signals using the Hermite functions as multiple windows, under randomly sampled or missing data. The multi-window sparse reconstruction approach improves energy concentration by utilizing the common local sparse frequency support property across the different employed windows.
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Branka Jokanović, Branka Jokanović, Moeness G. Amin, Moeness G. Amin, Yimin D. Zhang, Yimin D. Zhang, } "Sparse reconstruction of multi-window time-frequency representation based on Hermite functions", Proc. SPIE 9109, Compressive Sensing III, 910908 (23 May 2014); doi: 10.1117/12.2050797; https://doi.org/10.1117/12.2050797
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