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. In this paper, we apply non-linear Occam filters to broad-band signals. Using the chirp signal as a specific example, we find that the Occam filter outperforms the Wiener filter consistently.