modified akima piecewise cubic hermite interpolation Search Results


modified akima piecewise cubic hermite interpolation  (MathWorks Inc)
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MathWorks Inc modified akima piecewise cubic hermite interpolation
Modified Akima Piecewise Cubic Hermite Interpolation, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
modified akima piecewise cubic hermite interpolation - by Bioz Stars, 2026-03
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cubic spline data interpolation (spline)  (MathWorks Inc)
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MathWorks Inc cubic spline data interpolation (spline)
(Top) A single exponential decay function vs. time, representing the relaxation modulus of a single mode Maxwell fluid. (Bottom) A generic function resembling the normalised mean square displacement vs. time of an optically trapped particle suspended into a non-Newtonian fluid. Equations and are represented by a finite number of ‘sampled’ points and a continuous (pink) line. The points are also interpolated by means of three MATLAB built-in <t>interpolation</t> functions: Spline, PCHIP and Makima. The insets show the relative absolute error of each interpolation function with respect of either of Eqs. and , as calculated using Eq. . The time window of the inset encompasses the final three points of the main graph, where the relative error is at its highest.
Cubic Spline Data Interpolation (Spline), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/cubic spline data interpolation (spline)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
cubic spline data interpolation (spline) - by Bioz Stars, 2026-03
90/100 stars
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makima function  (MathWorks Inc)
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MathWorks Inc makima function
(Top) A single exponential decay function vs. time, representing the relaxation modulus of a single mode Maxwell fluid. (Bottom) A generic function resembling the normalised mean square displacement vs. time of an optically trapped particle suspended into a non-Newtonian fluid. Equations and are represented by a finite number of ‘sampled’ points and a continuous (pink) line. The points are also interpolated by means of three MATLAB built-in <t>interpolation</t> functions: Spline, PCHIP and Makima. The insets show the relative absolute error of each interpolation function with respect of either of Eqs. and , as calculated using Eq. . The time window of the inset encompasses the final three points of the main graph, where the relative error is at its highest.
Makima Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/makima function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
makima function - by Bioz Stars, 2026-03
90/100 stars
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(Top) A single exponential decay function vs. time, representing the relaxation modulus of a single mode Maxwell fluid. (Bottom) A generic function resembling the normalised mean square displacement vs. time of an optically trapped particle suspended into a non-Newtonian fluid. Equations and are represented by a finite number of ‘sampled’ points and a continuous (pink) line. The points are also interpolated by means of three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. The insets show the relative absolute error of each interpolation function with respect of either of Eqs. and , as calculated using Eq. . The time window of the inset encompasses the final three points of the main graph, where the relative error is at its highest.

Journal: Scientific Reports

Article Title: i-RheoFT: Fourier transforming sampled functions without artefacts

doi: 10.1038/s41598-021-02922-8

Figure Lengend Snippet: (Top) A single exponential decay function vs. time, representing the relaxation modulus of a single mode Maxwell fluid. (Bottom) A generic function resembling the normalised mean square displacement vs. time of an optically trapped particle suspended into a non-Newtonian fluid. Equations and are represented by a finite number of ‘sampled’ points and a continuous (pink) line. The points are also interpolated by means of three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. The insets show the relative absolute error of each interpolation function with respect of either of Eqs. and , as calculated using Eq. . The time window of the inset encompasses the final three points of the main graph, where the relative error is at its highest.

Article Snippet: Therefore, here we have compared the effectiveness of the following three interpolation functions already built-in MATLAB: a cubic spline data interpolation (Spline) (as the one used in ), a modified Akima piecewise cubic Hermite interpolation (Makima) and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) .

Techniques:

Mean relative absolute error (MRAE) vs. the density of initial experimental points (DIP) of the three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. (Top) The MRAE is evaluated with respect to Eq. . (Bottom) The MRAE is evaluated with respect to Eq. .

Journal: Scientific Reports

Article Title: i-RheoFT: Fourier transforming sampled functions without artefacts

doi: 10.1038/s41598-021-02922-8

Figure Lengend Snippet: Mean relative absolute error (MRAE) vs. the density of initial experimental points (DIP) of the three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. (Top) The MRAE is evaluated with respect to Eq. . (Bottom) The MRAE is evaluated with respect to Eq. .

Article Snippet: Therefore, here we have compared the effectiveness of the following three interpolation functions already built-in MATLAB: a cubic spline data interpolation (Spline) (as the one used in ), a modified Akima piecewise cubic Hermite interpolation (Makima) and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) .

Techniques:

Mean relative absolute error (MRAE) of the frequency-dependent complex moduli determined by Fourier transforming (via Eq. ) the interpolation functions shown in Fig. (top & bottom) for DIP values ranging from 1/4 to 1.

Journal: Scientific Reports

Article Title: i-RheoFT: Fourier transforming sampled functions without artefacts

doi: 10.1038/s41598-021-02922-8

Figure Lengend Snippet: Mean relative absolute error (MRAE) of the frequency-dependent complex moduli determined by Fourier transforming (via Eq. ) the interpolation functions shown in Fig. (top & bottom) for DIP values ranging from 1/4 to 1.

Article Snippet: Therefore, here we have compared the effectiveness of the following three interpolation functions already built-in MATLAB: a cubic spline data interpolation (Spline) (as the one used in ), a modified Akima piecewise cubic Hermite interpolation (Makima) and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) .

Techniques:

(Top) Eq. and (bottom) Eq. drawn as continuous (pink) lines by using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^4$$\end{document} 10 4 experimental points linearly spaced in time. A white noise having a SNR \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=50$$\end{document} = 50 is added to the experimental data, which are then interpolated by means of three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. The insets highlight the detrimental effects on the interpolation process due to the presence of noise, both at short and long time scales.

Journal: Scientific Reports

Article Title: i-RheoFT: Fourier transforming sampled functions without artefacts

doi: 10.1038/s41598-021-02922-8

Figure Lengend Snippet: (Top) Eq. and (bottom) Eq. drawn as continuous (pink) lines by using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^4$$\end{document} 10 4 experimental points linearly spaced in time. A white noise having a SNR \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=50$$\end{document} = 50 is added to the experimental data, which are then interpolated by means of three MATLAB built-in interpolation functions: Spline, PCHIP and Makima. The insets highlight the detrimental effects on the interpolation process due to the presence of noise, both at short and long time scales.

Article Snippet: Therefore, here we have compared the effectiveness of the following three interpolation functions already built-in MATLAB: a cubic spline data interpolation (Spline) (as the one used in ), a modified Akima piecewise cubic Hermite interpolation (Makima) and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) .

Techniques:

Mean relative absolute error (MRAE) of the frequency-dependent complex moduli determined by Fourier transforming (via Eq. ) the interpolation functions shown in Fig. (top & bottom respectively) for SNR values ranging from 1 to 350 dB. The error bars represent one standard deviation of uncertainty calculated over ten repeats.

Journal: Scientific Reports

Article Title: i-RheoFT: Fourier transforming sampled functions without artefacts

doi: 10.1038/s41598-021-02922-8

Figure Lengend Snippet: Mean relative absolute error (MRAE) of the frequency-dependent complex moduli determined by Fourier transforming (via Eq. ) the interpolation functions shown in Fig. (top & bottom respectively) for SNR values ranging from 1 to 350 dB. The error bars represent one standard deviation of uncertainty calculated over ten repeats.

Article Snippet: Therefore, here we have compared the effectiveness of the following three interpolation functions already built-in MATLAB: a cubic spline data interpolation (Spline) (as the one used in ), a modified Akima piecewise cubic Hermite interpolation (Makima) and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) .

Techniques: Standard Deviation