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Relevant bibliographies by topics / Entropy source

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Journal articles

Academic literature on the topic 'Entropy source'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Entropy source"

1

Flood, Matthew W., and Bernd Grimm. "EntropyHub: An open-source toolkit for entropic time series analysis." PLOS ONE 16, no. 11 (2021): e0259448. http://dx.doi.org/10.1371/journal.pone.0259448.

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An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods. To da

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2

Guyader, A., E. Fabre, C. Guillemot, and M. Robert. "Joint source-channel turbo decoding of entropy-coded sources." IEEE Journal on Selected Areas in Communications 19, no. 9 (2001): 1680–96. http://dx.doi.org/10.1109/49.947033.

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3

Chapeau-Blondeau, F., A. Delahaies, and D. Rousseau. "Source coding with Tsallis entropy." Electronics Letters 47, no. 3 (2011): 187. http://dx.doi.org/10.1049/el.2010.2792.

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4

Borysenko, Oleksiy. "ON COMBINATORIAL ENTROPY OF SOURCES OF BINARY INFORMATION." Grail of Science, no. 20 (October 6, 2022): 90–96. http://dx.doi.org/10.36074/grail-of-science.30.09.2022.017.

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The paper considers the question of converting the entropy of a probabilistic information source generating binary sequences into combinatorial forms of its two constituent sources. One of them is basic, and the second has a conditional entropy with respect to the first. It is shown that together such sources make it possible to optimally encode information using numbering at the efficiency level of known methods of optimal coding. In terms of their functions, they are universal and can solve all the problems that are solved by the methods of coding probabilistic sources. However, unlike them,

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5

Bercher, J. F. "Comment: Source coding with Tsallis entropy." Electronics Letters 47, no. 10 (2011): 597. http://dx.doi.org/10.1049/el.2011.0611.

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6

Răstoceanu, Florin, Răzvan Rughiniș, Ștefan-Dan Ciocîrlan, and Mihai Enache. "Sensor-Based Entropy Source Analysis and Validation for Use in IoT Environments." Electronics 10, no. 10 (2021): 1173. http://dx.doi.org/10.3390/electronics10101173.

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The IoT market has grown significantly in recent years, and it is estimated that it will continue to do so. For this reason, the need to identify new solutions to ensure security is vital for the future development in this field. Inadequate sources of entropy are one of the factors that negatively influence security. In this study, inspired by NIST’s latest entropy estimation recommendations, we proposed a methodology for analyzing and validating a sensor-based entropy source, highlighted by an innovative experiment design. Moreover, the proposed solution is analyzed in terms of resistance to

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7

Zhou, Li, and Yang Liu. "Optimization of Horizontal Plate Fin Heat Sink in Natural Convection for Electronics Cooling by Simulated Annealing Algorithm." Advanced Materials Research 1022 (August 2014): 91–95. http://dx.doi.org/10.4028/www.scientific.net/amr.1022.91.

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In this study, the simulated annealing (SA) algorithm was adopted to optimize the geometry of horizontal plate fin heat sink by the extreme entransy dissipation principle. The alculation of the entransy dissipation rate was presented in detail. Using the entransy dissipation rate as the objective condition, the geometry optimization of the fin heat sink was conducted. To verify the results, the heat source temperature and the entropy generation rate were also calculated in the procedure. It is found that the entrasy dissipation rate, entropy generation and heat source temperature have the simi

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8

Contreras Rodríguez, Lianet, Evaristo José Madarro-Capó , Carlos Miguel Legón-Pérez , Omar Rojas, and Guillermo Sosa-Gómez. "Selecting an Effective Entropy Estimator for Short Sequences of Bits and Bytes with Maximum Entropy." Entropy 23, no. 5 (2021): 561. http://dx.doi.org/10.3390/e23050561.

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Entropy makes it possible to measure the uncertainty about an information source from the distribution of its output symbols. It is known that the maximum Shannon’s entropy of a discrete source of information is reached when its symbols follow a Uniform distribution. In cryptography, these sources have great applications since they allow for the highest security standards to be reached. In this work, the most effective estimator is selected to estimate entropy in short samples of bytes and bits with maximum entropy. For this, 18 estimators were compared. Results concerning the comparisons publ

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9

Lopez-Sauceda, Juan, Philipp von Bülow, Carlos Ortega-Laurel, Francisco Perez-Martinez, Kalina Miranda-Perkins, and José Gerardo Carrillo González. "Entropy as a Geometrical Source of Information in Biological Organizations." Entropy 24, no. 10 (2022): 1390. http://dx.doi.org/10.3390/e24101390.

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Considering both biological and non-biological polygonal shape organizations, in this paper we introduce a quantitative method which is able to determine informational entropy as spatial differences between heterogeneity of internal areas from simulation and experimental samples. According to these data (i.e., heterogeneity), we are able to establish levels of informational entropy using statistical insights of spatial orders using discrete and continuous values. Given a particular state of entropy, we establish levels of information as a novel approach which can unveil general principles of b

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10

Silva, João B., Suzan S. Vasconcelos, and Valeria C. Barbosa. "Apparent-magnetization mapping using entropic regularization." GEOPHYSICS 75, no. 2 (2010): L39—L50. http://dx.doi.org/10.1190/1.3358160.

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A new apparent-magnetization mapping method on the horizontal plane combines minimization of first-order entropy with maximization of zeroth-order entropy of the estimated magnetization. The interpretation model is a grid of vertical, juxtaposed prisms in both horizontal directions. To estimate the magnetization of the prisms, assume that the top and bottom of the magnetic sources are horizontal. Minimization of the first-order entropy favors solutions with sharp borders, and the maximization of zeroth-order entropy prevents the tendency of the estimated source to become a single prism with la

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