Title of article
Integrating noisy data Original Research Article
Author/Authors
T. Prvan، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 1995
Pages
5
From page
83
To page
87
Abstract
Suppose the parametric form of a curve is not known, but only a set of observations. Quadrature formulae can be used to integrate a function only known from a set of data points. However, the results will be unreliable if the data contains measurement errors (noise). The method presented here fits an even degree piecewise polynomial to the data where all the data points are being used as knot points and the smoothing parameter is optimal for the indefinite integral of the curve which happens to be a smoothing spline. After the smoothing parameter has been chosen, this approach is less computationally expensive than fitting a smoothing spline and integrating.
Keywords
Kalman filter , Fixed-interval , Smoothing spline , Discrete-time smoother , Interpolation smoother
Journal title
Applied Mathematics Letters
Serial Year
1995
Journal title
Applied Mathematics Letters
Record number
896333
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