3. Interpolation and Curve Fitting

  1. Won Young Yang1,
  2. Wenwu Cao2,
  3. Tae-Sang Chung1 and
  4. John Morris3

Published Online: 27 JAN 2005

DOI: 10.1002/0471705195.ch3

Applied Numerical Methods Using MATLAB®

Applied Numerical Methods Using MATLAB®

How to Cite

Yang, W. Y., Cao, W., Chung, T.-S. and Morris, J. (2005) Interpolation and Curve Fitting, in Applied Numerical Methods Using MATLAB®, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471705195.ch3

Author Information

  1. 1

    Chung-Ang University, Korea

  2. 2

    Pennsylvania State University, USA

  3. 3

    The University of Auckland, New Zealand

Publication History

  1. Published Online: 27 JAN 2005
  2. Published Print: 14 JAN 2005

ISBN Information

Print ISBN: 9780471698333

Online ISBN: 9780471705192



  • interpolation;
  • curve fitting;
  • Lagrange polynomial;
  • Newton polynomial;
  • Chebyshev polynomial;
  • Pade approximation;
  • cubic spline;
  • Hermite interpolating polynomial;
  • 2-dimensional interpolation;
  • least-squares curve fitting;
  • weighted least-squares curve fitting;
  • Fourier transform;
  • FFT(fast Fourier transform);
  • DFT(Discrete Fourier Transform);
  • DFS(discrete Fourier series)


It introduces interpolation and curve fitting. Interpolation is to connect discrete data points so that one can get reasonable estimates of data points between the given points. Curve fitting is to find a curve that could best indicate the trend of a given set of data.