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Simulated and experimental verification for a terahertz specific finite rate of innovation signal processing method
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Barker, Xavier E. Ramirez, Stantchev, Rayko I., Hernandez Serrano, Arturo I. and Pickwell-MacPherson, Emma (2022) Simulated and experimental verification for a terahertz specific finite rate of innovation signal processing method. Sensors, 22 (9). 3387. doi:10.3390/s22093387 ISSN 1424-8220.
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WRAP-Simulated-and-experimental-verification-for-a-terahertz-specific-finite-rate-of-innovation-signal-processing-method-MacPherson-22.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1551Kb) | Preview |
Official URL: http://dx.doi.org/10.3390/s22093387
Abstract
Recently, finite rate of innovation methods have been successfully applied to achieve low sampling rates in many areas, such as for ultrasound and radio signals. However, to the best of our knowledge, there are no journal publications applying this to real terahertz signals. In this work, we mathematically describe a finite rate of innovation method applied specifically to terahertz signals both experimentally and in simulation. To demonstrate our method, we applied it to randomized simulated signals with and without the presence of noise and to simple experimental measurements. We found excellent agreement between the simulated signals and those recreated based on results from our method, with this success also being replicated experimentally. These results were obtained at relatively low sampling rates, compared to standard methods, which is a key advantage to using a finite rate of innovation method as it allows for faster data acquisition and signal processing.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | Q Science > QC Physics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Terahertz spectroscopy, Signal processing , Signal processing -- Digital techniques , Resonant ultrasound spectroscopy | ||||||||||||
| Journal or Publication Title: | Sensors | ||||||||||||
| Publisher: | MDPI AG | ||||||||||||
| ISSN: | 1424-8220 | ||||||||||||
| Official Date: | 28 April 2022 | ||||||||||||
| Dates: |
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| Volume: | 22 | ||||||||||||
| Number: | 9 | ||||||||||||
| Number of Pages: | 10 | ||||||||||||
| Article Number: | 3387 | ||||||||||||
| DOI: | 10.3390/s22093387 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
| Date of first compliant deposit: | 9 May 2022 | ||||||||||||
| Date of first compliant Open Access: | 9 May 2022 | ||||||||||||
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