Chapter 5
Interpolation
This chapter develops interpolation as the connection between discrete numerical data and continuous functions. It introduces polynomial interpolation, examines interpolation error and the Runge phenomenon, discusses Chebyshev node placement and finite-difference forms for equally spaced data, and develops cubic spline interpolation as a practical and stable approach for scientific computing.
In this chapter
- 5.1 What interpolation does
- 5.2 General polynomial interpolation
- 5.3 Spline interpolation
- 5.4 Interpolation versus data fitting
- 5.5 Summary and practical guidelines
- 5.6 Computational exercises and projects
Companion resources
Codes
MATLAB, Python, C++, and Fortran implementations of general polynomial interpolation, Runge/Chebyshev interpolation, and cubic spline interpolation.
View Chapter 5 codes →Exercises & Projects
Additional computational exercises, project ideas, and supporting material that extend the work in the chapter.
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Additional examples, practical notes, software links, and selected material related to interpolation.
View Chapter 5 resources →Updates & Errata
Corrections, clarifications, and post-publication updates associated with Chapter 5.
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