Chebyshev interpolation of an infinitely differentiable function on the given discrete computational grid
Approximation of an infinitely differentiable function based on the given discrete computational grid,
at intermediate evaluation points. The algorithm implements a more accurate version of the naive
polynomial interpolation, following
the paper Finding the Zeros of a Univariate Equation:
Proxy Rootfinders, Chebyshev Interpolation, and the Companion
Matrix by John P. Boyd.
Made as the Course Project 2 for Numerical Analysis and Scientific Computing-1 (MTH308B).
For functions with insanely large evaluation points, the observed accuracy improved by a factor of 10 trillion
as compared to the naive interpolation method,
after multiple runs on Matlab 2019a interpreter.
[1] JOHN P. BOYD, Finding the Zeros of a Univariate Equation…
[2] Wikipedia Contributers, Polynomial Interpolation, Wikipedia
Acknowledgment @kpsunil, for referencing the paper and the previous implementation.