Numerical differentiation of noisy data: a unifying multi-objective optimization framework

HIGHLIGHTS

  • who: FLORIS VAN BREUGEL and collaborators from the of Mechanical Engineering, University of Nevada at Reno, Reno, NV, USA have published the paper: Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework, in the Journal: (JOURNAL)
  • what: The authors take a principled approach propose a multi-objective optimization framework for choosing parameters that minimize a loss function to balance the faithfulness smoothness of the derivative estimate. Where ground-truth data is unknown the authors provide a heuristic for selecting this hyper-parameter based on the power spectrum temporal resolution of the data. The . . .

     

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