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Calculating mutual information for spike trains and other data with distances but no coordinates
1Department of Computer Science , University of Bristol, Merchant Venturers Building, Woodland Road , Bristol BS8 1UB, UK.
Abstract:
Many important data types, such as the spike trains recorded from neurons in typical electrophysiological experiments, have a natural notion of distance or similarity between data points, even though there is no obvious coordinate system. Here, a simple Kozachenko-Leonenko estimator is derived for calculating the mutual information between datasets of this type.
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