Numerical Differentiation of Experimental Data
نویسندگان
چکیده
منابع مشابه
Numerical differentiation of experimental data: local versus global methods
In the context of the analysis of measured data, one is often faced with the task to differentiate data numerically. Typically, this occurs when measured data are concerned or data are evaluated numerically during the evolution of partial or ordinary differential equations. Usually, one does not take care for accuracy of the resulting estimates of derivatives because modern computers are assume...
متن کاملMethods for Numerical Differentiation of Noisy Data
We describe several methods for the numerical approximation of a first derivative of a smooth real-valued univariate function for which only discrete noise-contaminated data values are given. The methods allow for both uniformly distributed and non-uniformly distributed abscissae. They are compared for accuracy on artificial data sets constructed by adding Gaussian noise to simple test function...
متن کاملNumerical 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...
متن کاملDynamic mode decomposition of numerical and experimental data
PETER J. SCHMID Journal of Fluid Mechanics / Volume 656 / August 2010, pp 5 28 DOI: 10.1017/S0022112010001217, Published online: 01 July 2010 Link to this article: http://journals.cambridge.org/abstract_S0022112010001217 How to cite this article: PETER J. SCHMID (2010). Dynamic mode decomposition of numerical and experimental data. Journal of Fluid Mechanics, 656, pp 528 doi:10.1017/S0022112...
متن کاملOn stable numerical differentiation
A new approach to the construction of finite-difference methods is presented. It is shown how the multi-point differentiators can generate regularizing algorithms with a stepsize h being a regularization parameter. The explicitly computable estimation constants are given. Also an iteratively regularized scheme for solving the numerical differentiation problem in the form of Volterra integral eq...
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ژورنال
عنوان ژورنال: Chemical engineering
سال: 1967
ISSN: 0375-9253
DOI: 10.1252/kakoronbunshu1953.31.509