Mark D. McDonnell

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Mark D. McDonnell
Person_Name: Mark D. McDonnell
Birth_Place: , Australia
Workplaces: University of Adelaide
High_School: [[]]
Undergrad_University: University of Adelaide
Doctoral_University: University of Adelaide
Doctoral_Degree: Electrical & Electronic Engineering ()
Doctoral_Advisors: Derek Abbott

Mark D. McDonnell

Bachelor's degree #1

  • Project:

Bachelor's degree #2

  • Project:

Doctoral degree

  • Electrical & Electronic Engineering (), University of Adelaide, Australia
  • Thesis: , under Derek Abbott



  • TBA

Scientific genealogy

Google Scholar profile

Book chapters

Journal articles

[1] L. Xu, F. Duan, D. Abbott, and M. D. McDonnell, "Adaptive recursive algorithm for optimal weighted suprathreshold stochastic resonance," Royal Society Open Science, Vol. 4, art. no. 160889, 2017, Scholar Google hits ResearchGate Academia

[2] L. J. Gunn, F. Chapeau-Blondeau, M. D. McDonnell, B. R. Davis, Andrew Allison and D. Abbott, "Too good to be true: when overwhelming evidence fails to convince," Proceedings of the Royal Society London A, Vol. 472, art. no. 20150748, 2016, Scholar Google hits ResearchGate Academia

[3] L. Xu, T. Vladusich, F. Duan, L. J. Gunn, D. Abbott and M. D. McDonnell, "Decoding suprathreshold stochastic resonance with optimal weights," Physics Letters A, Vol. 379, No. 38, pp. 2277–2283, 2015, Scholar Google hits ResearchGate

[4] M. D. McDonnell, A. J. Grant, I. Land, B. N. Vellambi, D. Abbott, and K. Lever, "Gain from the two-envelope problem via information asymmetry: on the suboptimality of randomized switching," Proceedings of the Royal Society London A, Vol. 467, pp. 2825–2851, 2011,

Conference articles

See also

External links