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AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

Qiuwen Chen, Ryan Luley, Qing Wu

    IEEE Transactions on Neural Networks and Learning Systems
    |March 23, 2017
    PubMed
    Summary

    This study introduces AnRAD, a bio-inspired framework for unsupervised anomaly detection in data streams. It offers high accuracy and real-time performance, leveraging parallel computing for efficient processing of complex patterns.

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