A memristor based neuromorphic processor for on-chip training is presented. Additionally, a novel approach utilizing in-situ learning to improve wireless signal modulation classification under adversarial jamming is described. The neuromorphic system is over 50× energy efficient than optimized digital systems at this wireless signal modulation task for similar accuracy levels.


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    Title :

    Memristor Based Online Learning Neuromorphic Processor for Adaptive Modulation Spectrum Sensing in Communication Jammed Environments


    Contributors:


    Publication date :

    2023-08-28


    Size :

    1265920 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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