Tackling faults in the industry 4.0 era—a survey of machine-learning solutions and key aspects
The recent advancements in the fields of artificial intelligence (AI) and machine learning
(ML) have affected several research fields, leading to improvements that could not have …
(ML) have affected several research fields, leading to improvements that could not have …
Feature selection and its use in big data: challenges, methods, and trends
M Rong, D Gong, X Gao - Ieee Access, 2019 - ieeexplore.ieee.org
Feature selection has been an important research area in data mining, which chooses a
subset of relevant features for use in the model building. This paper aims to provide an …
subset of relevant features for use in the model building. This paper aims to provide an …
Special session–machine learning in test: A survey of analog, digital, memory, and rf integrated circuits
Integrated circuit (IC) testing presents complex problems that, when ICs become large, are
exceptionally difficult to solve by traditional computing techniques. To deal with …
exceptionally difficult to solve by traditional computing techniques. To deal with …
A survey of digital circuit testing in the light of machine learning
M Pradhan, BB Bhattacharya - Wiley Interdisciplinary Reviews …, 2021 - Wiley Online Library
The insistent trend in today's nanoscale technology, to keep abreast of the Moore's law, has
been continually opening up newer challenges to circuit designers. With rapid downscaling …
been continually opening up newer challenges to circuit designers. With rapid downscaling …
Robust deep learning for ic test problems
Numerous machine learning (ML), and more recently, deep-learning (DL)-based
approaches, have been proposed to tackle scalability issues in electronic design …
approaches, have been proposed to tackle scalability issues in electronic design …
Board-level functional fault identification using streaming data
High integration densities and design complexity of printed-circuit boards make board-level
functional fault identification extremely difficult. Machine learning provides an opportunity to …
functional fault identification extremely difficult. Machine learning provides an opportunity to …
Fine-grained adaptive testing based on quality prediction
The ever-increasing complexity of integrated circuits inevitably leads to high test cost.
Adaptive testing provides an effective solution for test-cost reduction; this testing framework …
Adaptive testing provides an effective solution for test-cost reduction; this testing framework …
Knowledge transfer in board-level functional fault diagnosis enabled by domain adaptation
High integration densities and design complexity make board-level functional fault diagnosis
extremely difficult. Machine-learning techniques can identify functional faults with high …
extremely difficult. Machine-learning techniques can identify functional faults with high …
Unsupervised root-cause analysis for integrated systems
R Pan, Z Zhang, X Li, K Chakrabarty… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The increasing complexity and high cost of integrated systems has placed immense
pressure on root-cause analysis and diagnosis. In light of artificial intelligent and machine …
pressure on root-cause analysis and diagnosis. In light of artificial intelligent and machine …
Unsupervised two-stage root-cause analysis for integrated systems
R Pan, Z Zhang, X Li, K Chakrabarty… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The increasing complexity and high cost of integrated systems have placed immense
pressure on root-cause analysis and diagnosis. In light of artificial intelligence and machine …
pressure on root-cause analysis and diagnosis. In light of artificial intelligence and machine …