engleski

Sparse Time-Frequency Distribution Calculation with an Adaptive Thresholding Algorithm

Time-frequency distributions (TFD) are powerful tools for the analysis of non-stationary signals ; however they are heavily under-used since most of the TFD calculation methods introduce the unwanted artifacts, so called cross-terms. A recently investigated approach of the TFD cross-terms removal enforces the sparsity constraint to the resulting TFD, ultimately leading to a high resolution sparse TFD with heavily suppressed crossterms. In this paper, we apply a sparse reconstruction algorithm, which combines the fast intersection of the confidence intervals (FICI) rule and the two step iterative shrinkage/thresholding algorithm (TwIST), denoted as the FICI-TwIST algorithm, to modeled and real-life teleseismic signals. The obtained results have been compared, in terms of the resulting TFD concentration and the algorithm execution time, to the state-of-the-art sparse reconstruction algorithms.

Sparse time-frequency distributions, Ambiguity function, Compressive sensing, Fast intersection of confidence intervals (FICI) rule, Teleseismic signal

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