An algorithm for experimental data deconvolution using spline functions

DOI10.1016/0021-9991(83)90022-0zbMath0531.65077OpenAlexW1981039615MaRDI QIDQ788481

Paul Dierckx

Publication date: 1983

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0021-9991(83)90022-0

zbMATH Keywords

numerical examplesdata fittingspline approximationconvolution typecloseness of fitcomputer resultsexperimental data deconvolutionmeasuring devicesmoothness of approximationstatistics of errors

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Numerical methods for integral equations (65R20) Integral equations of the convolution type (Abel, Picard, Toeplitz and Wiener-Hopf type) (45E10)

Cites Work

• An algorithm for smoothing, differentiation and integration of experimental data using spline functions
• A practical guide to splines
• Smoothing by spline functions.
• On calculating with B-splines
• An Algorithm for Surface-Fitting with Spline Functions
• The Calculation of Indefinite Integrals of B-splines
• Least Squares Computations by Givens Transformations Without Square Roots
• The Numerical Evaluation of B-Splines

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