ECG-LDC: A Hardware-Efficient Low-Dimensional Computing Framework for ECG Arrhythmia Classification

2026-07-14T08:51:44Zec049599865ddaed1bf87a2e5166731db71b7a22fd1d963c242c9107a08dcb27
cross-environment-robustnessdevice-identificationiot-securityrf-fingerprinting

What happened

This arXiv feed contains multiple signal-processing and ML papers with clear security and privacy relevance. Notable items: (1) "Track-Consistency-Based GNSS RFI Monitoring Using Crowdsourced ADS-B Sensor Networks" demonstrates a scalable method to detect GNSS radio-frequency interference (RFI) events from 605M ADS‑B reports and found event clusters coincident with a NOTAM, indicating crowdsourced ADS‑B networks can provide complementary RFI situational awareness even when receiver quality indicators remain high. (2) "Physics‑Informed Structure Anchoring... for Cross‑Environment RF Fingerprint

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_eess_sp
Record identifier
ec049599865ddaed1bf87a2e5166731db71b7a22fd1d963c242c9107a08dcb27
Enrichment time
2026-07-14T08:51:44Z
AI-assisted enrichment
Yes

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Record · ECG-LDC: A Hardware-Efficient Low-Dimensional Computing Framework for ECG Arrhythmia Classification · Baitaphish