Results 1 to 10 of about 714,450 (192)
On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid [PDF]
Entropy, 2020 The Jensen−Shannon divergence is a renown bounded symmetrization of the Kullback−Leibler divergence which does not require probability densities to have matching supports. In this paper, we introduce a vector-skew generalization of the scalar
Frank Nielsen
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Fault Detection Based on Multi-Dimensional KDE and Jensen–Shannon Divergence [PDF]
Entropy, 2021 Weak fault signals, high coupling data, and unknown faults commonly exist in fault diagnosis systems, causing low detection and identification performance of fault diagnosis methods based on T2 statistics or cross entropy. This paper proposes a new fault
Juhui Wei +4 more
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On the Jensen–Shannon Symmetrization of Distances Relying on Abstract Means [PDF]
Entropy, 2019 The Jensen–Shannon divergence is a renowned bounded symmetrization of the unbounded Kullback–Leibler divergence which measures the total Kullback–Leibler divergence to the average mixture distribution.
Frank Nielsen
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Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence [PDF]
Frontiers in Oncology, 2021 MotivationThe evolution of complex diseases can be modeled as a time-dependent nonlinear dynamic system, and its progression can be divided into three states, i.e., the normal state, the pre-disease state and the disease state.
Jinling Yan +7 more
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Entropy, 2021 We generalize the Jensen-Shannon divergence and the Jensen-Shannon diversity index by considering a variational definition with respect to a generic mean, thereby extending the notion of Sibson’s information radius.
Frank Nielsen
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Entropy, 2021 In this work, we first consider the discrete version of Fisher information measure and then propose Jensen–Fisher information, to develop some associated results.
Omid Kharazmi +1 more
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Quantifying the Dissimilarity of Texts
Information, 2023 Quantifying the dissimilarity of two texts is an important aspect of a number of natural language processing tasks, including semantic information retrieval, topic classification, and document clustering.
Benjamin Shade, Eduardo G. Altmann
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Refined Young Inequality and Its Application to Divergences
Entropy, 2021 We give bounds on the difference between the weighted arithmetic mean and the weighted geometric mean. These imply refined Young inequalities and the reverses of the Young inequality. We also studied some properties on the difference between the weighted
Shigeru Furuichi, Nicuşor Minculete
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A method for continuous-range sequence analysis with Jensen-Shannon divergence
Papers in Physics, 2021 Mutual Information (MI) is a useful Information Theory tool for the recognition of mutual dependence between data sets. Several methods have been developed fore estimation of MI when both data sets are of the discrete type or when both are of the ...
Miguel Ángel Ré +1 more
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Technologies, 2021 The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution ...
Antonios Lionis +3 more
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