RRAM Crossbar-Based Fault-Tolerant Binary Neural Networks (BNNs)
Author:
Affiliation:
1. Computer Engineering Lab, Delft University of Technology,Delft,The Netherlands
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9810327/9810358/09810414.pdf?arnumber=9810414
Reference14 articles.
1. ISAAC
2. Mish: A self regularized non-monotonic neural activation function;misra;ArXiv,2019
3. Activation functions in neural networks;sharma;Towards Data Science,2017
4. Fault and Error Tolerance in Neural Networks: A Review
5. Handling stuck-at-faults in memristor crossbar arrays using matrix transformations
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2. Analysis of Conductance Variability in RRAM for Accurate Neuromorphic Computing;2024 IEEE 25th Latin American Test Symposium (LATS);2024-04-09
3. Online Fault-Tolerance for Memristive Neuromorphic Fabric Based on Local Approximation;2023 IEEE European Test Symposium (ETS);2023-05-22
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