Machine Learning Methodologies to Predict the Results of Simulation-Based Fault Injection
Author:
Affiliation:
1. IHP-Leibniz-Institut für innovative Mikroelektronik, Frankfurt (Oder), Germany
Funder
German Federal Ministry of Education through the Project Scale4Edge
Project VE-HEP
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/8919/10510354/10390537.pdf?arnumber=10390537
Reference42 articles.
1. Selective Hardening: Toward Cost-Effective Error Tolerance
2. A survey on fault injection techniques;Ziade;Int. Arab J. Inf. Technol.,2004
3. Towards acceleration of fault simulation using graphics processing units
4. GPU-accelerated fault simulation and its new applications
5. Multi-level timing and fault simulation on GPUs
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1. Guest Editorial: Special Issue on Learning, Optimization, and Implementation for Circuits and Systems Driven by Artificial Intelligence;IEEE Transactions on Circuits and Systems I: Regular Papers;2024-05
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