Machine Learning Approaches for Analysis of Total Ionizing Dose in Microelectronics
Author:
Affiliation:
1. University of Tennessee at Chattanooga, Vanderbilt University
2. University of Tennessee at Chattanooga,615 McCallie Ave., Dept. 2342,Chattanooga,TN,USA,37403
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10412245/10412349/10412523.pdf?arnumber=10412523
Reference13 articles.
1. Total Ionizing Dose Effects on Commercial Electronics for Cube Sats in Low Earth Orbits
2. Using Benchmarks for Radiation Testing of Microprocessors and FPGAs
3. Radiation Specification and Testing of Heterogenous Microprocessor SOCs
4. Investigation of TID and Dynamic Burn-In-Induced $V_{{T}}$ Shift on RTG4 Flash-Based FPGA
5. Response of a 22FDX® Radiation-Hardened-by-Design Test Chip to TID and SEE
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