Noise Reduction for Experimental Data
نویسنده
چکیده
We introduce an algorithm for nonlinear noise reduction which is based on locally linear ts to the nonlinear dynamics. We claim that it is both robust and exible enough to apply it to a variety of experimental time series. In the second part of the paper we show its performance on data set A. The correlation dimension, Liapunov exponent and the Poincar e map are computed before and after the noise reduction.
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