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Abstract
This paper introduces an adaptive frequency sampling scheme, based on a Bayesian approach to the well-known vector fitting algorithm. This Bayesian treatment results in a data-driven measure of intrinsic model uncertainty. This uncertainty measure can in turn be leveraged to sample sequentially in an efficient and robust way. A realistic example is used to visualize the proposed scheme, and to confirm its proficiency.
Keywords
Bayes methods, sampling methods, ALGORITHM

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Citation

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MLA
De Ridder, Simon, et al. “A Bayesian Approach to Adaptive Frequency Sampling.” 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019), IEEE, 2019.
APA
De Ridder, S., Deschrijver, D., Spina, D., Dhaene, T., & Vande Ginste, D. (2019). A Bayesian approach to adaptive frequency sampling. In 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019). Chamberry, France: IEEE.
Chicago author-date
De Ridder, Simon, Dirk Deschrijver, Domenico Spina, Tom Dhaene, and Dries Vande Ginste. 2019. “A Bayesian Approach to Adaptive Frequency Sampling.” In 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019). IEEE.
Chicago author-date (all authors)
De Ridder, Simon, Dirk Deschrijver, Domenico Spina, Tom Dhaene, and Dries Vande Ginste. 2019. “A Bayesian Approach to Adaptive Frequency Sampling.” In 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019). IEEE.
Vancouver
1.
De Ridder S, Deschrijver D, Spina D, Dhaene T, Vande Ginste D. A Bayesian approach to adaptive frequency sampling. In: 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019). IEEE; 2019.
IEEE
[1]
S. De Ridder, D. Deschrijver, D. Spina, T. Dhaene, and D. Vande Ginste, “A Bayesian approach to adaptive frequency sampling,” in 2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019), Chamberry, France, 2019.
@inproceedings{8628907,
  abstract     = {{This paper introduces an adaptive frequency sampling scheme, based on a Bayesian approach to the well-known vector fitting algorithm. This Bayesian treatment results in a data-driven measure of intrinsic model uncertainty. This uncertainty measure can in turn be leveraged to sample sequentially in an efficient and robust way. A realistic example is used to visualize the proposed scheme, and to confirm its proficiency.}},
  author       = {{De Ridder, Simon and Deschrijver, Dirk and Spina, Domenico and Dhaene, Tom and Vande Ginste, Dries}},
  booktitle    = {{2019 23RD IEEE WORKSHOP ON SIGNAL AND POWER INTEGRITY (SPI 2019)}},
  isbn         = {{2475-9481}},
  keywords     = {{Bayes methods,sampling methods,ALGORITHM}},
  language     = {{eng}},
  location     = {{Chamberry, France}},
  publisher    = {{IEEE}},
  title        = {{A Bayesian approach to adaptive frequency sampling}},
  url          = {{http://dx.doi.org/10.1109/SaPIW.2019.8781640}},
  year         = {{2019}},
}

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