Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems

Author:

Schuman Catherine D.,Parker Mitchell J.,Johnston J. Travis,Parsa Maryam,Kay Bill,Date Prasanna,Patton Robert M.

Publisher

IEEE

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Leveraging Sparsity of SRNNs for Reconfigurable and Resource-Efficient Network-on-Chip;2024 Neuro Inspired Computational Elements Conference (NICE);2024-04-23

2. NoisyDECOLLE: Robust Local Learning for SNNs on Neuromorphic Hardware;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15

3. Testing and Reliability of Spiking Neural Networks: A Review of the State-of-the-Art;2023 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT);2023-10-03

4. On-Line Testing of Neuromorphic Hardware;2023 IEEE European Test Symposium (ETS);2023-05-22

5. A Reliability Assessment Approach for A LIF Neurons Based Spiking Neural Network Circuit;2023 24th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE);2023-04-17

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