Kulkarni, Pranav and Vaidyanathan, P. P. (2021) Periodic Signal Denoising: An Analysis-Synthesis Framework Based on Ramanujan Filter Banks and Dictionaries. In: 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE , Piscataway, NJ, pp. 5100-5104. ISBN 9781728176055. https://resolver.caltech.edu/CaltechAUTHORS:20210602-093734579
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Abstract
Ramanujan filter banks (RFB) have in the past been used to identify periodicities in data. These are analysis filter banks with no synthesis counterpart for perfect reconstruction of the original signal, so they have not been useful for denoising periodic signals. This paper proposes to use a hybrid analysis-synthesis framework for denoising discrete-time periodic signals. The synthesis occurs via a pruned dictionary designed based on the output energies of the RFB analysis filters. A unique property of the framework is that the denoised output signal is guaranteed to be periodic unlike any of the other methods. For a large range of input noise levels, the proposed approach achieves a stable and high SNR gain outperforming many traditional denoising techniques.
Item Type: | Book Section | ||||||||
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Additional Information: | © 2021 IEEE. This work was supported in parts by the ONR Grant N00014-18-1-2390, the NSF Grant CCF-1712633, and the California Institute of Technology. | ||||||||
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Subject Keywords: | Periodicity, denoising, Ramanujan filter banks, pruned synthesis dictionary, hidden periods | ||||||||
DOI: | 10.1109/ICASSP39728.2021.9413689 | ||||||||
Record Number: | CaltechAUTHORS:20210602-093734579 | ||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20210602-093734579 | ||||||||
Official Citation: | P. Kulkarni and P. P. Vaidyanathan, "Periodic Signal Denoising: An Analysis-Synthesis Framework Based on Ramanujan Filter Banks and Dictionaries," ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, pp. 5100-5104, doi: 10.1109/ICASSP39728.2021.9413689 | ||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||
ID Code: | 109338 | ||||||||
Collection: | CaltechAUTHORS | ||||||||
Deposited By: | Tony Diaz | ||||||||
Deposited On: | 02 Jun 2021 17:11 | ||||||||
Last Modified: | 02 Jun 2021 17:11 |
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