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Barua extracting high resolution harmonic fingerprinting from sparse sampling to disaggregate complex CVDs

05.08.26 | George Mason University

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Barua Extracting High Resolution Harmonic Fingerprinting From Sparse Sampling to Disaggregate Complex CVDs

Anomadarshi Barua, Assistant Professor, Cyber Security Engineering, College of Engineering and Computing (CEC), received funding for the project: “Extracting High Resolution Harmonic Fingerprinting FromSparse Sampling to Disaggregate Complex CVDs.”

Barua aims to advance predictive maintenance and diagnostics of naval subsystems using power signatures without intrusive sensors. They also aim to enhance current naval energy systems by extracting hidden, high-frequency load features from existing low-rate logs. By doing so, they assert they will open new directions to advance compressed sensing, model-based reconstruction, and low-rate machine learning. Moreover, upon success, their work can be trained on full-spectrum sonar returns to predict missing high-band information from lower-band signals. This will give “virtual high-resolution” SONAR over longer ranges.

Barua received $175,000 from the Office of Naval Research for this project. Funding began in April 2026 and will end in late March 2031 with a total awarded amount of $840,000.

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Contact Information

Elizabeth Grisham
George Mason University
egrisham@gmu.edu

How to Cite This Article

APA:
George Mason University. (2026, May 8). Barua extracting high resolution harmonic fingerprinting from sparse sampling to disaggregate complex CVDs. Brightsurf News. https://www.brightsurf.com/news/19N6N791/barua-extracting-high-resolution-harmonic-fingerprinting-from-sparse-sampling-to-disaggregate-complex-cvds.html
MLA:
"Barua extracting high resolution harmonic fingerprinting from sparse sampling to disaggregate complex CVDs." Brightsurf News, May. 8 2026, https://www.brightsurf.com/news/19N6N791/barua-extracting-high-resolution-harmonic-fingerprinting-from-sparse-sampling-to-disaggregate-complex-cvds.html.