Memristor-Based Neuromorphic System for Unsupervised Online Learning and Network Anomaly Detection on Edge Devices
An ultralow-power, high-performance online-learning and anomaly-detection system has been developed for edge security applications. Designed to support personalized learning without relying on cloud data processing, the system employs sample-wise learning, eliminating the need for storing entire dat...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2025-03-01
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| Col·lecció: | Information |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2078-2489/16/3/222 |
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