Interpolation techniques for noisy spectral data
A technique for interpolating noisy frequency domain data is presented. It is based on rational function interpolation with the least square error method. Compared to traditional Lagrange interpolation, the method is shown to be more robust. Results for simulated data with additive white Gaussian noise and measured data are presented to demonstrate the validity of the interpolation technique.<<ETX>>