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Relevant bibliographies by topics / Entropy methods

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Academic literature on the topic 'Entropy methods'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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Journal articles on the topic "Entropy methods"

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Chinenye Ezeh, Chinenye Ezeh, Tao Ren Chinenye Ezeh, Yan-Jie Xu Tao Ren, Shi-Xiang Sun Yan-Jie Xu, and Zhe Li Shi-Xiang Sun. "Entropy and Structural-Hole Based Node Ranking Methods." 網際網路技術學刊 22, no. 5 (2021): 1009–17. http://dx.doi.org/10.53106/160792642021092205007.

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Lozano, Carlos. "Entropy and Adjoint Methods." Journal of Scientific Computing 81, no. 3 (2019): 2447–83. http://dx.doi.org/10.1007/s10915-019-01092-0.

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Temursho, Umed. "Entropy-based benchmarking methods." Statistica Neerlandica 72, no. 4 (2018): 421–46. http://dx.doi.org/10.1111/stan.12160.

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Osara, Jude A., and Michael D. Bryant. "Methods to Calculate Entropy Generation." Entropy 26, no. 3 (2024): 237. http://dx.doi.org/10.3390/e26030237.

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Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real-time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, interna

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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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SHAMILOV, Aladdin, and Nihal İNCE. "On Several New Generalized Entropy Optimization Methods." Turkiye Klinikleri Journal of Biostatistics 8, no. 2 (2016): 110–15. http://dx.doi.org/10.5336/biostatic.2016-52369.

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Dobrzynski, L. "Bayesian and Maximum Entropy Methods." Physica Scripta 79, no. 4 (2008): 040201. http://dx.doi.org/10.1088/0031-8949/79/4/040201.

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TAIMRE, THOMAS. "ADVANCES IN CROSS-ENTROPY METHODS." Bulletin of the Australian Mathematical Society 80, no. 3 (2009): 521–22. http://dx.doi.org/10.1017/s0004972709000781.

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Brereton, R. G. "Entropy methods in chemical dataprocessing." Chemometrics and Intelligent Laboratory Systems 12, no. 3 (1991): 305–7. http://dx.doi.org/10.1016/0169-7439(92)80016-w.

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Alizadeh Noughabi, Hadi. "Entropy Estimation Using Numerical Methods." Annals of Data Science 2, no. 2 (2015): 231–41. http://dx.doi.org/10.1007/s40745-015-0045-9.

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Dissertations / Theses on the topic "Entropy methods"

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Kim, Sangil. "Ensemble Filtering Methods for Nonlinear Dynamics." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1101%5F1%5Fm.pdf&type=application/pdf.

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Hughes, Leslie Peter. "Maximum entropy methods applied to NMR and mass spectrometry." Thesis, Durham University, 2001. http://etheses.dur.ac.uk/3785/.

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Maximum Entropy data processing techniques have been widely available for use by NMR spectroscopisis and mass spectrometrisls since they were first reported as a tool for enhancing damaged images. However, the techniques have been met with a certain amount of scepticism amongst the spectroscopic community; not least their apparent ability to get something for nothing. The aim of the work presented in this thesis is to demonstrate that if these techniques are used carefully and in appropriate situations a great deal of information can be extracted from both NMR and mass spectra. This has been a

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Basile, Chiara <1982&gt. "Entropy and Semantics: Textual Information Extraction through Statistical Methods." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amsdottorato.unibo.it/3224/1/Basile_Chiara_tesi.pdf.

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Basile, Chiara <1982&gt. "Entropy and Semantics: Textual Information Extraction through Statistical Methods." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amsdottorato.unibo.it/3224/.

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Von, Lorne von Saint Ange Chantel. "Integration of ranking and selection methods with the multi-objective optimisation cross-entropy method." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/97072.

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Thesis (MEng)--Stellenbosch University, 2015.<br>ENGLISH ABSTRACT: A method for multi-objective optimisation using the cross-entropy method (MOO CEM) was recently developed by Bekker & Aldrich (2010) and Bekker (2012). The method aims to identify the nondominated solutions of multi-objective problems, which are often dynamic and stochastic. The method does not use a statistical ranking and selection technique to account for the stochastic nature of the problems it solves. The research in this thesis aims to investigate possible techniques that can be incorporated into the MOO CEM. The

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Straka, Mika Julian. "Entropy-based methods for the statistical validation of bipartite networks." Thesis, IMT Alti Studi Lucca, 2018. http://e-theses.imtlucca.it/253/1/Straka_phdthesis.pdf.

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Bipartite networks provide an insightful representation of many complex systems, ranging from mutualistic species interactions in ecology to financial investment portfolios of banks. In order to unveil genuine properties of real-world structures, statistical comparisons with appropriately defined null models are necessary. Among other frameworks, entropy-based null models have proven to perform satisfactorily in providing benchmarks for testing evidence-based hypotheses, showing the desirable feature that the resulting graph probability distributions are generally unbiased and often a

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Parisi, Federica. "Entropy-based methods to tackle missing information in complex networks." Thesis, IMT Alti Studi Lucca, 2019. http://e-theses.imtlucca.it/269/1/Parisi_phdthesis.pdf.

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The work presented in this thesis focuses on an issue that very commonly arise when studying a network: missing information. There are many phenomena that can cause such a lack of knowledge, but prior to any attempt at studying the data, it is desirable to have a knowledge of the network at hand that is as complete as possible. Here I will address specifically two types of missing information problems, namely network reconstruction and link prediction. In the former case, the network structure is hidden, the only information we have access to is the size of the network and some aggrega

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Chan, Oscar. "Prosodic features for a maximum entropy language model." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0244.

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A statistical language model attempts to characterise the patterns present in a natural language as a probability distribution defined over word sequences. Typically, they are trained using word co-occurrence statistics from a large sample of text. In some language modelling applications, such as automatic speech recognition (ASR), the availability of acoustic data provides an additional source of knowledge. This contains, amongst other things, the melodic and rhythmic aspects of speech referred to as prosody. Although prosody has been found to be an important factor in human speech recognitio

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Tate, Graeme. "New methods in protein X-ray crystallography using maximum entropy techniques." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396507.

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Johnson, Jason K. (Jason Kyle). "Convex relaxation methods for graphical models : Lagrangian and maximum entropy approaches." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45871.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.<br>Includes bibliographical references (p. 241-257).<br>Graphical models provide compact representations of complex probability distributions of many random variables through a collection of potential functions defined on small subsets of these variables. This representation is defined with respect to a graph in which nodes represent random variables and edges represent the interactions among those random variables. Graphical models provide a powerful and flexible approach to man

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Books on the topic "Entropy methods"

1

Maximum Entropy Workshop (8th 1988 St. John's College). Maximum entropy and Bayesian methods, Cambridge, England, 1988. Kluwer Academic Publishers, 1989.

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Erickson, Gary J., Joshua T. Rychert, and C. Ray Smith, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5028-6.

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Hanson, Kenneth M., and Richard N. Silver, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-5430-7.

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Heidbreder, Glenn R., ed. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8729-7.

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Skilling, J., ed. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-7860-8.

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Fougère, Paul F., ed. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0683-9.

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Grandy, W. T., and L. H. Schick, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3460-6.

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Mohammad-Djafari, Ali, and Guy Demoment, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-017-2217-9.

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Smith, C. Ray, Gary J. Erickson, and Paul O. Neudorfer, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-017-2219-3.

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Skilling, John, and Sibusiso Sibisi, eds. Maximum Entropy and Bayesian Methods. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0107-0.

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Book chapters on the topic "Entropy methods"

1

Barbakh, Wesam Ashour, Ying Wu, and Colin Fyfe. "Cross Entropy Methods." In Non-Standard Parameter Adaptation for Exploratory Data Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04005-4_9.

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Cho, Shinil. "Entropy." In Mathematical Methods for Physics using Microsoft EXCEL. CRC Press, 2025. https://doi.org/10.1201/9781003516347-5.

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Marti, Kurt. "Maximum Entropy Techniques." In Stochastic Optimization Methods. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46214-0_8.

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Marti, Kurt. "Maximum Entropy Techniques." In Stochastic Optimization Methods. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-40059-9_13.

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Zhang, Yong. "Preparation Methods of High-Entropy Materials." In High-Entropy Materials. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8526-1_3.

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Jüngel, Ansgar. "Towards Discrete Entropy Methods." In Entropy Methods for Diffusive Partial Differential Equations. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-34219-1_5.

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Popkov, Yuri S., Alexey Yu Popkov, Yuri A. Dubnov, and Alexander Yu Mazurov. "Dimension Reduction Methods." In Entropy Randomization in Machine Learning. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003306566-3.

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Bajkova, A. T. "Generalized Maximum Entropy. Comparison with Classical Maximum Entropy." In Maximum Entropy and Bayesian Methods. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-017-2217-9_50.

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Skilling, John. "Classic Maximum Entropy." In Maximum Entropy and Bayesian Methods. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-7860-8_3.

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Jowitt, P. W. "Entropy + Rain = Floods." In Maximum Entropy and Bayesian Methods. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-7860-8_46.

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Conference papers on the topic "Entropy methods"

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Hall, Keith, and Richard Sproat. "Russian Stress Prediction using Maximum Entropy Ranking." In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2013. http://dx.doi.org/10.18653/v1/d13-1088.

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Grendar, M. "Empirical Maximum Entropy Methods." In Bayesian Inference and Maximum Entropy Methods In Science and Engineering. AIP, 2006. http://dx.doi.org/10.1063/1.2423302.

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Caticha, Ariel, Kevin H. Knuth, Ariel Caticha, Julian L. Center, Adom Giffin, and Carlos C. Rodríguez. "Information and Entropy." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING. AIP, 2007. http://dx.doi.org/10.1063/1.2821253.

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Chockler, Hana, Eitan Farchi, Benny Godlin, and Sergey Novikov. "Cross-Entropy Based Testing." In Formal Methods in Computer Aided Design (FMCAD'07). IEEE, 2007. http://dx.doi.org/10.1109/fmcad.2007.4401988.

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Chockler, Hana, Eitan Farchi, Benny Godlin, and Sergey Novikov. "Cross-Entropy Based Testing." In Formal Methods in Computer Aided Design (FMCAD'07). IEEE, 2007. http://dx.doi.org/10.1109/famcad.2007.19.

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Sukumar, N. "Maximum Entropy Approximation." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2005. http://dx.doi.org/10.1063/1.2149812.

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Cheeseman, Peter. "Generalized Maximum Entropy." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2005. http://dx.doi.org/10.1063/1.2149816.

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"Entropy based Biometric Template Clustering." In International Conference on Pattern Recognition Applications and Methods. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004266205600563.

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Juhász, Gergely, Ferenc Hareancz, Enikő Réka Fábián, and Ádám Vida. "Production Methods of High-Entropy Alloys." In 9th International Scientific Conference on Advances in Mechanical Engineering. Trans Tech Publications Ltd, 2024. http://dx.doi.org/10.4028/p-abd8zw.

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High-entropy alloys (HEAs) are a new and rapidly developing area of materials science, characterized by their high entropy content. High-entropy alloys have received considerable attention in recent years because of their properties, such as high tensile strength, corrosion resistance and excellent heat resistance. These materials have the potential to broaden material utilization in aerospace, automotive, energy, and other industries. There are three main manufacturing technology group to produce high entropy alloys. These groups are melting and casting, powder metallurgy, and deposition tech

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Toma, Cristian E., and Mihai P. Datcu. "Maximum entropy and minimum cross-entropy methods in image processing." In Applications in Optical Science and Engineering, edited by Hatem N. Nasr and Rodney M. Larson. SPIE, 1993. http://dx.doi.org/10.1117/12.143059.

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Reports on the topic "Entropy methods"

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Silver, R. N., H. Roeder, A. F. Voter, and J. D. Kress. Chebyshev recursion methods: Kernel polynomials and maximum entropy. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/119974.

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Silver, R. N., H. Roeder, A. F. Voter, and J. D. Kress. Chebyshev moment problems: Maximum entropy and kernel polynomial methods. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/195578.

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Larimore, Wallace E. Development of Statistical Methods Using Predictive Inference and Entropy. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada185459.

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Torres, Jesus V., Alfredo Cruz, and Jeff Duffany. How Do Statistical Detection Methods Compare to Entropy Measures. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada585591.

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Walmsley, Terrie, and Robert McDougall. Using Entropy to Compare IO tables. GTAP Research Memoranda, 2005. http://dx.doi.org/10.21642/gtap.rm09.

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The importance of obtaining quality I-O tables for the GTAP Data Base has prompted the need for a method to compare contributed I-O tables. Comparisons are useful for a number of reasons. a) Time comparisons can be used to show how an economy has changed over time. b) Country comparisons may be used to show differences in cost or use structures between countries. c) Comparisons may also be used to highlight errors in construction procedures or mappings and therefore assist us in improving the quality of the data. In this document we look out how entropy can be used to compare I-O tables. The p

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Soloviev, Vladimir, and Andrey Belinskij. Methods of nonlinear dynamics and the construction of cryptocurrency crisis phenomena precursors. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2851.

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This article demonstrates the possibility of constructing indicators of critical and crisis phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex systems such as recurrent analysis of dynamic systems and the calculation of permutation entropy are used. It is shown that it is possible to construct dynamic measures of complexity, both recurrent and entropy, which behave in a proper way during actual pre-crisis periods. This fact is used to build predictors of crisis phenomena on the example of the main five crises recorded in the time series o

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Zilberman, Mark. Good and Evil from the Point of View of Physics. Intellectual Archive, 2022. http://dx.doi.org/10.32370/iaj.2763.

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The article analyzes the concepts of "good" and "evil" from the point of view of physics. Although the physical concept of “entropy” as a measure of disorder was the first candidate who could serve as the physical basis of these ethical concepts, in fact it is not suitable for this purpose. However, the “entropic potential of the event” Z (T, A) that describes the impact of the event A that occurred in the moment T0 in the system R to the entropy of this system at the future moment T (T > T0) is well suited for our analysis. The article describes methods for calculating the “entropic potent

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Glasscott, Matthew. Classifying and benchmarking high-entropy alloys and associated materials for electrocatalysis : a brief review of best practices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48082.

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In light of the immense compositional diversity of high-entropy materials (HEMs) recently reported (e.g., high-entropy chalcogenides, perovskites, ceramics, etc.) and the relatively amorphous definition of High-Entropy, it is imperative that consistent material classification and benchmarking practices be employed to facilitate comparison between reported figures of merit. In this opinion, an updated form of the numerical high-entropy definition is reviewed, which renders a universal entropy metric applicable to high-entropy alloys and emerging HEMs alike. Analytical methods to verify the exis

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Soloviev, Vladimir N., Andrii O. Bielinskyi, and Natalia A. Kharadzjan. Coverage of the Coronavirus Pandemic through Entropy Measures. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4427.

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The rapidly evolving coronavirus pandemic brings a devastating effect on the entire world and its economy as awhole. Further instability related to COVID-19will negatively affect not only on companies and financial markets, but also on traders and investors that have been interested in saving their investment, minimizing risks, and making decisions such as how to manage their resources, how much to consume and save, when to buy or sell stocks, etc., and these decisions depend on the expectation of when to expect next critical change. Trying to help people in their subsequent decisions, we demo

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Шарапов, О. Д., та В. М. Соловйов. Використання вейвлет-ентропії для аналізу складних економічних систем. КНЕУ, 2008. http://dx.doi.org/10.31812/0564/1322.

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У роботі розглянуто методи розрахунку значень вейвлет-ентропії на основі дискретного та неперервного вейвлет-перетворення. За допомогою описаних методів проведено аналіз трьох економічних криз минулого сторіччя та зроблено висновки щодо можливості використання вейвлет-ентропії для дослідження економічних систем з точки зору наявності в їх функціонуванні критичних та кризових явищ. This paper Is devoted to the methods of calculation of values wavelet entropy based on discrete and continuous wavelet-transformation. By the described methods the analysis of three economic crises of past century is

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