Numerical Interpolation & Differentiation

版本 2.0.0 (40.5 KB) 作者: Samiu Haque
Interpolate and Differentiate numerical datasets by generating a function for equal interval using Newton Forward/Backward & Sterling Method
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更新时间 2021/3/18

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NumericalDifferentiation

This MATLAB program is designed to analyze datasets by generating a function based on the provided data. It then conducts differentiation on the generated function. The program utilizes Newton's Forward/Backward Difference and Stirling's method for this purpose, which requires that the interval of the independent variable remains consistent across the dataset.

Here's a summary of the steps the program takes:

    Function Generation: The program evaluates the provided datasets to generate a function that approximates the relationship between the independent and dependent variables. It uses techniques like Newton's Forward/Backward Difference and Stirling's method.
    Differentiation: The program performs differentiation up to a specified order on the generated function.
    Evaluation: After differentiation, the program allows users to evaluate either the original function or its derivative at specified points of interest.
    Note on Interval: The datasets must have equal intervals for the independent variable to ensure accurate results when using techniques like Newton's Forward/Backward Difference and Stirling's method.

引用格式

Samiu Haque (2024). Numerical Interpolation & Differentiation (https://www.mathworks.com/matlabcentral/fileexchange/80158-numerical-interpolation-differentiation), MATLAB Central File Exchange. 检索来源 .

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创建方式 R2019a
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版本 已发布 发行说明
2.0.0

Live Editor Version

1.0.0

See release notes for this release on GitHub: https://github.com/SamiuHaque/NumericalDifferentiation/releases/tag/v1.0
See release notes for this release on GitHub: https://github.com/SamiuHaque/NumericalDifferentiation/releases/tag/v1.0.0

See release notes for this release on GitHub: https://github.com/SamiuHaque/NumericalDifferentiation/releases/tag/v1.0.0
See release notes for this release on GitHub: https://github.com/SamiuHaque/NumericalDifferentiation/releases/tag/v1.0