Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework
نویسندگان
چکیده
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Numerical Differentiation of Noisy, Nonsmooth Data
In many scientific applications, it is necessary to compute the derivative of functions specified by data. Conventional finite-difference approximations will greatly amplify any noise present in the data. Denoising the data before or after differentiating does not generally give satisfactory results see an example in Section 4 . A method which does give good results is to regularize the differe...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.3034077