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%.
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| http://dx.doi.org/10.1103/PhysRevE.80.016207 | DOI Listing |
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