A highly reliable and tamper-resistant RRAM PUF: Design and experimental validation
Rui Liu(Arizona State University), Shimeng Yu(Georgia Institute of Technology), Huaqiang Wu(Beijing Advanced Sciences and Innovation Center), Yachun Pang(Institute of Microelectronics), He Qian(University of Science and Technology of China)
Cited by 61
Related Papers
Fully hardware-implemented memristor convolutional neural network
|Nature|2020|2.2k
Face classification using electronic synapses
|Nature Communications|2017|909
Neuro-inspired computing chips
|Nature Electronics|2020|886
A compute-in-memory chip based on resistive random-access memory
|Nature|2022|882