Results 11 to 20 of about 105,427 (308)
First Digits’ Shannon Entropy [PDF]
Entropy, 2022 Related to the letters of an alphabet, entropy means the average number of binary digits required for the transmission of one character. Checking tables of statistical data, one finds that, in the first position of the numbers, the digits 1 to 9 occur ...
Welf Alfred Kreiner
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Shannon entropy and particle decays [PDF]
Nuclear Physics B, 2018 We deploy Shannon's information entropy to the distribution of branching fractions in a particle decay. This serves to quantify how important a given new reported decay channel is, from the point of view of the information that it adds to the already ...
Pedro Carrasco Millán +4 more
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Perceptual Complexity as Normalized Shannon Entropy [PDF]
EntropyComplexity is one of the most important variables in how the brain performs decision making based on esthetic values. Multiple definitions of perceptual complexity have been proposed, with one of the most fruitful being the Normalized Shannon Entropy one.
Norberto M. Grzywacz
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Infinite Shannon entropy [PDF]
Journal of Statistical Mechanics: Theory and Experiment, 2013 Even if a probability distribution is properly normalizable, its associated Shannon (or von Neumann) entropy can easily be infinite. We carefully analyze conditions under which this phenomenon can occur.
Baccetti, Valentina, Visser, Matt
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Statistical estimation of conditional Shannon entropy [PDF]
ESAIM: Probability and Statistics, 2018 The new estimates of the conditional Shannon entropy are introduced in the framework of the model describing a discrete response variable depending on a vector ofdfactors having a density w.r.t. the Lebesgue measure in ℝd. Namely, the mixed-pair model (X,Y) is considered whereXandYtake values in ℝdand an arbitrary finite set, respectively.
Alexander Bulinski, Alexey Kozhevin
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On Convergence Properties of Shannon Entropy [PDF]
Problems of Information Transmission, 2007 Convergence properties of Shannon Entropy are studied. In the differential setting, it is shown that weak convergence of probability measures, or convergence in distribution, is not enough for convergence of the associated differential entropies.
A. Antos +16 more
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Application of Positional Entropy to Fast Shannon Entropy Estimation for Samples of Digital Signals [PDF]
Entropy, 2020 This paper introduces a new method of estimating Shannon entropy. The proposed method can be successfully used for large data samples and enables fast computations to rank the data samples according to their Shannon entropy.
Marcin Cholewa, Bartłomiej Płaczek
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Shannon Entropy Loss in Mixed-Radix Conversions [PDF]
Entropy, 2021 This paper models a translation for base-2 pseudorandom number generators (PRNGs) to mixed-radix uses such as card shuffling. In particular, we explore a shuffler algorithm that relies on a sequence of uniformly distributed random inputs from a mixed ...
Amy Vennos, Alan Michaels
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Renyi extrapolation of Shannon entropy [PDF]
Open Systems & Information Dynamics, 2003 Relations between Shannon entropy and Rényi entropies of integer order are discussed. For any N-point discrete probability distribution for which the Rényi entropies of order two and three are known, we provide a lower and an upper bound for the Shannon entropy. The average of both bounds provide an explicit extrapolation for this quantity.
Karol Życzkowski
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Spatial distribution of the Shannon entropy for mass spectrometry imaging [PDF]
PLoS ONE, 2023 Mass spectrometry imaging (MSI) allows us to visualize the spatial distribution of molecular components in a sample. A large amount of mass spectrometry data comprehensively provides molecular distributions.
Lili Xu +13 more
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