Machine Learning Support for Diagnosis of Analog Circuits-Reference-Cited by-同舟云学术

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Machine Learning Support for Diagnosis of Analog Circuits

Published:2022-10-22 Issue: Volume: Page:205-245
ISSN:
Container-title:Machine Learning Support for Fault Diagnosis of System-on-Chip
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Author:

Stratigopoulos Haralampos-G.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-19639-3_7

Reference133 articles.

1. Abdallah, L., Stratigopoulos, H.G., Mir, S., Kelma, C.: Experiences with non-intrusive sensors for RF built-in test. In: Proceedings of the IEEE International Test Conference, Paper 17.1 (2012).

2. Abdallah, L., Stratigopoulos, H.G., Mir, S., Altet, J.: Defect-oriented non-intrusive RF test using on-chip temperature sensors. In: Proceedings of the IEEE VLSI Test Symposium (2013)

3. Ahmadi, A., Stratigopoulos, H.G., Huang, K., Nahar, A., Orr, B., Pas, M., Carulli, J.M., Makris, Y.: Yield forecasting across semiconductor fabrication plants and design generations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36(12), 2120–2133 (2017)

4. Akbay, S.S., Chatterjee, A.: Fault-based alternate test of RF components. In: IEEE International Conference on Computer Design, pp. 518–525 (2007)

5. Akbay, S.S., Halder, A., Chatterjee, A., Keezer, D.: Low-cost test of embedded RF/Analog/Mixed-signal circuits in SOPs. IEEE Trans. Adv. Packag. 27(2), 352–363 (2004)

Cited by 2 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. Analog Circuit Fault Diagnosis Based on Machine Learning Using Frequency Domain Features;2024 11th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN);2024-06-03

2. Analog Circuit Fault Diagnosis Based on the Fractional Sliding Model Observer;Circuits, Systems, and Signal Processing;2023-06-28

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