Topology-based Signal Separation
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Robins, Vanessa; Rooney, Niall; Bradley, Elizabeth
Description
Traditional noise-filtering techniques are known to significantly alter features of chaotic data. In this paper, we present a noncausal topology-based filtering method for continuous-time dynamical systems that is effective in removing additive, uncorrelated noise from time-series data. Signal-to-noise ratios and Lyapunov exponent estimates are dramatically improved following the removal of the identified noisy points.
Collections | ANU Research Publications |
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Date published: | 2004 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/77658 |
Source: | Chaos An Interdisciplinary Journal of Nonlinear Science |
DOI: | 10.1063/1.1705852 |
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