On-Line Testing of Neuromorphic Hardware

Author:

Spyrou Theofilos1,Stratigopoulos Haralampos-G.1

Affiliation:

1. Sorbonne Université,CNRS, LIP6,Paris,France

Publisher

IEEE

Reference26 articles.

1. Machine Learning-Based Test Pattern Generation for Neuromorphic Chips

2. ReSpawn: Energy-efficient fault-tolerance for spiking neural networks considering unreliable memories;putra;Proc ACM/IEEE Int Conf Comput -Aided Design (ICCAD),2021

3. SoftSNN

4. Neuron fault tolerance in spiking neural networks;spyrou;Proc Design and Test in Europe (DATE) Conf,2021

5. Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems

Cited by 4 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. A Survey on Neuromorphic Architectures for Running Artificial Intelligence Algorithms;Electronics;2024-07-26

2. Artificial Neural Networks for Space and Safety-Critical Applications: Reliability Issues and Potential Solutions;IEEE Transactions on Nuclear Science;2024-04

3. Signature Driven Post-Manufacture Testing and Tuning of RRAM Spiking Neural Networks for Yield Recovery;2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22

4. 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

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