Test results for leveled inverse interpolation

Figures 27 and 28 show the same example as in Figures and . What is new here is that the proper PEF is not given but is determined from the data. Figure 27 was made with a three-coefficient filter (1,a₁,a₂) and Figure 28 was made with a five-coefficient filter (1,a₁,a₂,a₃,a₄). The main difference in the figures is where the data is sparse. The data points in Figures , 27 and 28 are samples from a sinusoid.

 

subsine390 Figure 27 Interpolating with a three-term filter. The interpolated signal is fairly monofrequency.

 

subsine590 Figure 28 Interpolating with a five term filter.

Comparing Figures and to Figures 27 and 28 we conclude that by finding and imposing the prediction-error filter while finding the model space, we have interpolated beyond aliasing in data space.