Abstract
The stair-like structure in the correlation integral of measured data is investigated. It is shown that the stairs are caused by the limited floating-point accuracy of the data in the measurement, and are completely different from the noise in the measured phenomenon. It is found that a modified singular value decomposition filter with very large projection dimension can improve the precision of the data and smooth the stairs in the correlation integral.
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