Identifying Good-Dice-in-Bad-Neighborhoods Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Identifying Good-Dice-in-Bad-Neighborhoods Using Artificial Neural Networks

Published:2024-08 Issue:3 Volume:37 Page:280-292
ISSN:0894-6507
Container-title:IEEE Transactions on Semiconductor Manufacturing
language:
Short-container-title:IEEE Trans. Semicond. Manufact.

Author:

Yen Chia-Heng¹^ORCID,Wang Ting-Rui¹,Liu Ching-Min²,Yang Cheng-Hao²,Chen Chun-Teng³,Chen Ying-Yen³,Lee Jih-Nung³^ORCID,Kao Shu-Yi³,Wu Kai-Chiang⁴,Chao Mango Chia-Tso⁵

Affiliation:

1. Institute of Computer Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

2. Institute of Data Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

3. CTC/DFT, Realtek Semiconductor Corp., Hsinchu, Taiwan

4. Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

5. Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/66/10636181/10540253.pdf?arnumber=10540253

Reference26 articles.

1. Stuck-open and transition fault testing in CMOS complex gates

2. Defect-oriented cell-aware ATPG and fault simulation for industrial cell libraries and designs

3. Methodology of generating dual-cell-aware tests

4. Small Delay Fault Model for Intra-Gate Resistive Open Defects

5. Highly Accelerated Temperature and Humidity Stress Test Technique (HAST)

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