Results 41 to 50 of about 22,391 (177)
Seven Means, Generalized Triangular Discrimination, and Generating Divergence Measures
Information, 2013 Jensen-Shannon, J-divergence and Arithmetic-Geometric mean divergences are three classical divergence measures known in the information theory and statistics literature.
Inder Jeet Taneja
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EURASIP Journal on Advances in Signal Processing, 2004 Heterogeneous DNA sequences can be partitioned into homogeneous domains that are comprised of the four nucleotides A, C, G, and T and the stop-codons.
Daniel Nicorici, Jaakko Astola
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Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach [PDF]
, 2006 High-frequency financial data of the foreign exchange market (EUR/CHF, EUR/GBP, EUR/JPY, EUR/NOK, EUR/SEK, EUR/USD, NZD/USD, USD/CAD, USD/CHF, USD/JPY, USD/NOK, and USD/SEK) are analyzed by utilizing the Kullback-Leibler divergence between two normalized
Aiba +27 more
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An Entropy Formulation Based on the Generalized Liouville Fractional Derivative
Entropy, 2019 This paper presents a new formula for the entropy of a distribution, that is conceived having in mind the Liouville fractional derivative. For illustrating the new concept, the proposed definition is applied to the Dow Jones Industrial Average. Moreover,
Rui A. C. Ferreira, J. Tenreiro Machado
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Wootters' distance revisited: a new distinguishability criterium [PDF]
, 2004 The notion of distinguishability between quantum states has shown to be fundamental in the frame of quantum information theory. In this paper we present a new distinguishability criterium by using a information theoretic quantity: the Jensen-Shannon ...
A. Majtey +19 more
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Genome Biology, 2020 In population genomics, genetic diversity measures play an important role in genome scans for divergent sites. In population epigenomics, comparable tools are rare although the epigenome can vary at several levels of organization. We propose a model-free,
Önder Kartal +2 more
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Graph Complexity from the Jensen-Shannon Divergence [PDF]
, 2012 In this paper we aim to characterize graphs in terms of structural complexities. Our idea is to decompose a graph into substructures of increasing layers, and then to measure the dissimilarity of these substructures using Jensen-Shannon divergence.
Lu Bai, Edwin R. Hancock
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FSMJ: Feature Selection with Maximum Jensen-Shannon Divergence for Text Categorization
, 2016 In this paper, we present a new wrapper feature selection approach based on Jensen-Shannon (JS) divergence, termed feature selection with maximum JS-divergence (FSMJ), for text categorization.
He, Haibo, Tang, Bo
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Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain
Advanced Science, EarlyView.A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio +3 more
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A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data
Advanced Science, EarlyView.SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang +5 more
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