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.
Memristor Based Online Learning Neuromorphic Processor for Adaptive Modulation Spectrum Sensing in Communication Jammed Environments
28.08.2023
1265920 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Integration of nanoscale memristor synapses in neuromorphic computing architectures
BASE | 2013
|GWLB - Gottfried Wilhelm Leibniz Bibliothek | 2000
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