Using Machine Learning to Correct Probe Skew in High-frequency Electrical Loss Measurements

Wang, Jun (Principal Investigator)
Liu, Song (Co-Investigator)

Status	Finished
Effective start/end date	20/11/23 → 31/05/24
Links	https://jeangoldinginstitute.blogs.bristol.ac.uk/2024/09/13/using-machine-learning-to-correct-probe-skew-in-high-frequency-electrical-loss-measurements/

Access Project

https://jeangoldinginstitute.blogs.bristol.ac.uk/2024/09/13/using-machine-learning-to-correct-probe-skew-in-high-frequency-electrical-loss-measurements/

1 Article (Academic Journal)

Machine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements
Wang, Y., Liu, S., Wang, J., Cui, B. & Yang, J., 1 Oct 2025, In: IEEE Transactions on Power Electronics. 40, 10, p. 14356-14362 7 p.
Research output: Contribution to journal › Article (Academic Journal) › peer-review

Open Access
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2 Citations (Scopus)

69 Downloads (Pure)

Outstanding Performance Award 3rd Place, MagNet Challenge 2023
Wang, J. (Recipient), McKeague, T. (Recipient), Zhang, L. (Recipient), Cui, B. (Recipient) & Liu, S. (Recipient), 28 Feb 2024
Prize: Prizes, Medals, Awards and Grants