A General Framework for Generative Self-supervised Learning in Non-invasive Estimation of Physiological Parameters Using Photoplethysmography
arXiv 2604.22780•66aad34596ce1c7538f1ebd2ce6916eda851f1f9d180c4f591158dcc3d0041e1
AI-safetyLCXPPGQCMRF-interferenceantenna-reconfigurationautoregressive-modelsbiosensingcovert-communicationsdual-useinterference-mitigationradio-mappingreconfigurable-antennassensor-robustnesssignal-processingsoft-fusionsparse-arraysspectrum-operationstransformer-modelstri-hybrid-MIMOwireless-security
Paper metadata
- arXiv ID
- 2604.22780
- Version
- Not specified by this published record
- Category
- Electrical Engineering and Systems Science — Signal Processing (eess.SP)
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Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 66aad34596ce1c7538f1ebd2ce6916eda851f1f9d180c4f591158dcc3d0041e1
- Enrichment time
- 2026-04-28T08:51:47Z
- AI-assisted enrichment
- Yes
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