Reduction of noise of large amplitude through adaptive neighborhoods.

We propose a noise reduction algorithm based on adaptive neighborhood selection that is able to obtain high levels of noise reduction for chaotic vector time series corrupted by observational noises with a noise-to-signal ratio of up to 300%.