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Leveraging Emerging Technology for Hardware Security - Case Study on Silicon Nanowire FETs and Graphene SymFETs.

, , , , , and . ATS, page 342-347. IEEE Computer Society, (2014)

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On the use of random walks to estimate correlation in fitness landscapes, and . Computational Statistics & Data Analysis, 28 (2): 131--137 (Aug 7, 1998)Application-level Studies of Cellular Neural Network-based Hardware Accelerators., , , , , and . CoRR, (2019)FeCAM: A Universal Compact Digital and Analog Content Addressable Memory Using Ferroelectric., , , , , , , and . CoRR, (2020)Seed-and-Vote based In-Memory Accelerator for DNA Read Mapping., , , , , and . ICCAD, page 56:1-56:9. IEEE, (2020)Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators Through Training with Right-Censored Gaussian Noise., , , , and . ICCAD, page 1-9. IEEE, (2023)Computing-In-Memory Neural Network Accelerators for Safety-Critical Systems: Can Small Device Variations Be Disastrous?, , and . ICCAD, page 87:1-87:9. ACM, (2022)A Hybrid FeMFET-CMOS Analog Synapse Circuit for Neural Network Training and Inference., , , , , and . ISCAS, page 1-5. IEEE, (2020)Enhancing Hardware Security with Emerging Transistor Technologies., , , , , and . ACM Great Lakes Symposium on VLSI, page 305-310. ACM, (2016)Reducing Delay Jitter of Real-Time Control Tasks through Adaptive Deadline Adjustments., , and . ECRTS, page 229-238. IEEE Computer Society, (2010)Period and Deadline Selection for Schedulability in Real-Time Systems., , , and . ECRTS, page 168-177. IEEE Computer Society, (2008)