
arXiv: 1709.10153
handle: 11336/65552 , 11086/553676
Jensen-Shannon divergence is a well known multi-purpose measure of dissimilarity between probability distributions. It has been proven that the square root of this quantity is a true metric in the sense that, in addition to the basic properties of a distance, it also satisfies the triangle inequality. In this work we extend this last result to prove that in fact it is possible to derive a monoparametric family of metrics from the classical Jensen-Shannon divergence. Motivated by our results, an application into the field of symbolic sequences segmentation is explored. Additionally, we analyze the possibility to extend this result into the quantum realm.
8 pages, 4 figures
Information theory, Measures of information, entropy, 330, Spaces of measures, convergence of measures, Information Theory, Quantum Distances, FOS: Physical sciences, Mathematical Physics (math-ph), Jensen-Shannon Divergence, metrics, Jensen-Shannon divergence, quantum distances, Quantum distances, https://purl.org/becyt/ford/1.3, Metrics, Probabilistic measure theory, https://purl.org/becyt/ford/1, Mathematical Physics, information theory
Information theory, Measures of information, entropy, 330, Spaces of measures, convergence of measures, Information Theory, Quantum Distances, FOS: Physical sciences, Mathematical Physics (math-ph), Jensen-Shannon Divergence, metrics, Jensen-Shannon divergence, quantum distances, Quantum distances, https://purl.org/becyt/ford/1.3, Metrics, Probabilistic measure theory, https://purl.org/becyt/ford/1, Mathematical Physics, information theory
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