Comparing Occam and Wiener filters on broad-band signals

Occam filters are a class of filters for additive random noise, based on the idea that when a lossy data compression algorithm is applied to a noisy signal with the allowed loss set equal to the noise strength, the loss and the noise tend to cancel rather than add. The authors apply non-linear Occam filters to broad-band signals. Using the chirp signal as a specific example, they find that the Occam filter outperforms the Wiener filter consistently