Quantized Non-Volatile Nanomagnetic Synapse based Autoencoder for Efficient Unsupervised Network Anomaly Detection

no code implementations • 12 Sep 2023 • Muhammad Sabbir Alam, Walid Al Misba, Jayasimha Atulasimha

While the limited number of quantized states and the inherent stochastic nature of DW synaptic weights in nanoscale devices are known to negatively impact the performance, our hardware-aware training algorithm is shown to leverage these imperfect device characteristics to generate an improvement in anomaly detection accuracy (90. 98%) compared to accuracy obtained with floating-point trained weights.

Anomaly Detection