Abstract
Using a small dataset resulting from a new optical engineering technique for the fingerprinting of beverages and other liquids, we develop and study an approach to quantitatively characterizing the inherent information in our data. To do this we use properties of the data which are related to resolution scale and noise. We demonstrate the effectiveness of such intelligent data modeling.
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Murtagh, F., Starck, JL., McMillan, N., Campbell, J.G. (2000). Intelligent Data Modeling Based on the Wavelet Transform and Data Entropy. In: Gaul, W., Opitz, O., Schader, M. (eds) Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58250-9_22
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DOI: https://doi.org/10.1007/978-3-642-58250-9_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67731-4
Online ISBN: 978-3-642-58250-9
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