Conclusions

I have implemented Spitz's interpolation method and tested it on real and synthetic data. This method is based upon two theoretical properties of linear events, the first of which is the predictability along the x direction of such events in the $({\omega},x)$ domain. The second property is that the filters predicting the interpolated data at the frequency $\omega$ also predict the original data at the frequency ${\omega}/n$ if an n^th order interpolation is to be considered. The results show that the method performs well when the data has significant energy in the lower part of the spectrum; on the contrary if the energy is concentrated at above half the Nyquist frequency, the method performs poorly.