arXiv (All)
open access
When Does Spatial Cooperation Help? Contamination Regimes in Decentralized Online Spectrum Anomaly Learning
Learning-based spectrum monitors adapt online to benign propagation changes, but persistent rogue transmissions can gradually become incorporated into the learned background. Spatially distributed receivers provide additional evidence for detecting such anomalies, while decentralized model mixing ca
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Integrating local spatial outliers into context-aware spatial prediction models#398547
- Sampling for Region-Aggregated Spatial Scan Statistics#793760
- Sampling for Region-Aggregated Spatial Scan Statistics#789755
- A Gram-Attention Learning Framework for Spatially Non-Stationary Channel Estimation#1062330
- Can We Predict Anomaly Detection Performance from Embedding-Space Geometry?#1062351
Record · ID 1536362
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive