Littérature scientifique sur le sujet « Entropy algorithms »
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Articles de revues sur le sujet "Entropy algorithms"
Li, Yancang, et Wanqing Li. « Adaptive Ant Colony Optimization Algorithm Based on Information Entropy : Foundation and Application ». Fundamenta Informaticae 77, no 3 (janvier 2007) : 229–42. https://doi.org/10.3233/fun-2007-77303.
Texte intégralTurlykozhayeva, D. A. « ROUTING METRIC AND PROTOCOL FOR WIRELESS MESH NETWORK BASED ON INFORMATION ENTROPY THEORY ». Eurasian Physical Technical Journal 20, no 4 (46) (19 décembre 2023) : 90–98. http://dx.doi.org/10.31489/2023no4/90-98.
Texte intégralZhang, Chuang, Yue-Han Pei, Xiao-Xue Wang, Hong-Yu Hou et Li-Hua Fu. « Symmetric cross-entropy multi-threshold color image segmentation based on improved pelican optimization algorithm ». PLOS ONE 18, no 6 (29 juin 2023) : e0287573. http://dx.doi.org/10.1371/journal.pone.0287573.
Texte intégralManis, George, Md Aktaruzzaman et Roberto Sassi. « Low Computational Cost for Sample Entropy ». Entropy 20, no 1 (13 janvier 2018) : 61. http://dx.doi.org/10.3390/e20010061.
Texte intégralLiu, Jing, Huibin Lu, Xiuru Zhang, Xiaoli Li, Lei Wang, Shimin Yin et Dong Cui. « Which Multivariate Multi-Scale Entropy Algorithm Is More Suitable for Analyzing the EEG Characteristics of Mild Cognitive Impairment ? » Entropy 25, no 3 (21 février 2023) : 396. http://dx.doi.org/10.3390/e25030396.
Texte intégralJi, Binghui, Xiaona Sun, Peimiao Chen, Siyu Wang, Shangfa Song et Bo He. « An Integrated Navigation Algorithm for Underwater Vehicles Improved by a Variational Bayesian and Minimum Mixed Error Entropy Unscented Kalman Filter ». Electronics 13, no 23 (29 novembre 2024) : 4727. http://dx.doi.org/10.3390/electronics13234727.
Texte intégralDu, Xinzhi. « A Robust and High-Dimensional Clustering Algorithm Based on Feature Weight and Entropy ». Entropy 25, no 3 (16 mars 2023) : 510. http://dx.doi.org/10.3390/e25030510.
Texte intégralMorozov, Denys. « Polynomial Representation of Binary Trees of Entropy Binary Codes ». Mohyla Mathematical Journal 4 (19 mai 2022) : 20–23. http://dx.doi.org/10.18523/2617-70804202120-23.
Texte intégralCrysdian, Cahyo. « The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge ». JOIV : International Journal on Informatics Visualization 7, no 4 (31 décembre 2023) : 2481. http://dx.doi.org/10.62527/joiv.7.4.1727.
Texte intégralCrysdian, Cahyo. « The Evaluation of Entropy-based Algorithm towards the Production of Closed-Loop Edge ». JOIV : International Journal on Informatics Visualization 7, no 4 (31 décembre 2023) : 2481. http://dx.doi.org/10.30630/joiv.7.4.01727.
Texte intégralThèses sur le sujet "Entropy algorithms"
Höns, Robin. « Estimation of distribution algorithms and minimum relative entropy ». [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980407877.
Texte intégralLuo, Shen. « Interior-Point Algorithms Based on Primal-Dual Entropy ». Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/1181.
Texte intégralFellman, Laura Suzanne. « The Genetic Algorithm and Maximum Entropy Dice ». PDXScholar, 1996. https://pdxscholar.library.pdx.edu/open_access_etds/5247.
Texte intégralMeehan, Timothy J. « Joint demodulation of low-entropy narrow band cochannel signals ». Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FMeehan%5FPhD.pdf.
Texte intégralDissertation supervisor(s): Frank E. Kragh. "December 2006." Includes bibliographical references (p. 167-177). Also available in print.
Reimann, Axel. « Evolutionary algorithms and optimization ». Doctoral thesis, [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=969093497.
Texte intégralJIMMY, TJEN. « Entropy-Based Sensor Selection Algorithms for Damage Detection in SHM Systems ». Doctoral thesis, Università degli Studi dell'Aquila, 2021. http://hdl.handle.net/11697/173561.
Texte intégralKirsch, Matthew Robert. « Signal Processing Algorithms for Analysis of Categorical and Numerical Time Series : Application to Sleep Study Data ». Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1278606480.
Texte intégralMolari, Marco. « Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data ». Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/6160/.
Texte intégralKotha, Aravind Eswar Ravi Raja, et Lakshmi Ratna Hima Rajitha Majety. « Performance Comparison of Image Enhancement Algorithms Evaluated on Poor Quality Images ». Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13880.
Texte intégralSaraiva, Gustavo Francisco Rosalin. « Análise temporal da sinalização elétrica em plantas de soja submetidas a diferentes perturbações externas ». Universidade do Oeste Paulista, 2017. http://bdtd.unoeste.br:8080/jspui/handle/jspui/1087.
Texte intégralMade available in DSpace on 2018-07-27T17:57:40Z (GMT). No. of bitstreams: 1 Gustavo Francisco Rosalin Saraiva.pdf: 5041218 bytes, checksum: 30127a7816b12d3bd7e57182e6229bc2 (MD5) Previous issue date: 2017-03-31
Plants are complex organisms with dynamic processes that, due to their sessile way of life, are influenced by environmental conditions at all times. Plants can accurately perceive and respond to different environmental stimuli intelligently, but this requires a complex and efficient signaling system. Electrical signaling in plants has been known for a long time, but has recently gained prominence with the understanding of the physiological processes of plants. The objective of this thesis was to test the following hypotheses: temporal series of data obtained from electrical signaling of plants have non-random information, with dynamic and oscillatory pattern, such dynamics being affected by environmental stimuli and that there are specific patterns in responses to stimuli. In a controlled environment, stressful environmental stimuli were applied in soybean plants, and the electrical signaling data were collected before and after the application of the stimulus. The time series obtained were analyzed using statistical and computational tools to determine Frequency Spectrum (FFT), Autocorrelation of Values and Approximate Entropy (ApEn). In order to verify the existence of patterns in the series, classification algorithms from the area of machine learning were used. The analysis of the time series showed that the electrical signals collected from plants presented oscillatory dynamics with frequency distribution pattern in power law. The results allow to differentiate with great efficiency series collected before and after the application of the stimuli. The PSD and autocorrelation analyzes showed a great difference in the dynamics of the electric signals before and after the application of the stimuli. The ApEn analysis showed that there was a decrease in the signal complexity after the application of the stimuli. The classification algorithms reached significant values in the accuracy of pattern detection and classification of the time series, showing that there are mathematical patterns in the different electrical responses of the plants. It is concluded that the time series of bioelectrical signals of plants contain discriminant information. The signals have oscillatory dynamics, having their properties altered by environmental stimuli. There are still mathematical patterns built into plant responses to specific stimuli.
As plantas são organismos complexos com processos dinâmicos que, devido ao seu modo séssil de vida, sofrem influência das condições ambientais todo o tempo. Plantas podem percebem e responder com precisão a diferentes estímulos ambientais de forma inteligente, mas para isso se faz necessário um complexo e eficiente sistema de sinalização. A sinalização elétrica em plantas já é conhecida há muito tempo, mas vem ganhando destaque recentemente com seu entendimento em relação aos processos fisiológicos das plantas. O objetivo desta tese foi testar as seguintes hipóteses: séries temporais de dados obtidos da sinalização elétrica de plantas possuem informação não aleatória, com padrão dinâmico e oscilatório, sendo tal dinâmica afetada por estímulos ambientais e que há padrões específicos nas respostas a estímulos. Em ambiente controlado, foram aplicados estímulos ambientais estressantes em plantas de soja, e captados os dados de sinalização elétrica antes e após a aplicação dos mesmos. As séries temporais obtidas foram analisadas utilizando ferramentas estatísticas e computacionais para se determinar o Espectro de Frequências (FFT), Autocorrelação dos valores e Entropia Aproximada (ApEn). Para se verificar a existência de padrões nas séries, foram utilizados algoritmos de classificação da área de aprendizado de máquina. A análise das séries temporais mostrou que os sinais elétricos coletados de plantas apresentaram dinâmica oscilatória com padrão de distribuição de frequências em lei de potência. Os resultados permitem diferenciar com grande eficácia séries coletadas antes e após a aplicação dos estímulos. As análises de PSD e autocorrelação mostraram grande diferença na dinâmica dos sinais elétricos antes e após a aplicação dos estímulos. A análise de ApEn mostrou haver diminuição da complexidade do sinal após a aplicação dos estímulos. Os algoritmos de classificação alcançaram valores significativos na acurácia de detecção de padrões e classificação das séries temporais, mostrando haver padrões matemáticos nas diferentes respostas elétricas das plantas. Conclui-se que as séries temporais de sinais bioelétricos de plantas possuem informação discriminante. Os sinais possuem dinâmica oscilatória, tendo suas propriedades alteradas por estímulos ambientais. Há ainda padrões matemáticos embutidos nas respostas da planta a estímulos específicos.
Livres sur le sujet "Entropy algorithms"
National Institute of Standards and Technology (U.S.), dir. Parallel algorithms for entropy-coding techniques. Gaithersburg, MD : U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1998.
Trouver le texte intégralSantos, Cícero Nogueira dos. Entropy guided transformation learning : Algorithms and applications. London : Springer, 2012.
Trouver le texte intégraldos Santos, Cícero Nogueira, et Ruy Luiz Milidiú. Entropy Guided Transformation Learning : Algorithms and Applications. London : Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2978-3.
Texte intégralLuiz, Milidiu Ruy, et SpringerLink (Online service), dir. Entropy Guided Transformation Learning : Algorithms and Applications. London : Springer London, 2012.
Trouver le texte intégralPríncipe, J. C. Information theoretic learning : Renyi's entropy and kernel perspectives. New York : Springer, 2010.
Trouver le texte intégralM, Le Thinh, Lian Yong et SpringerLink (Online service), dir. Entropy Coders of the H.264/AVC Standard : Algorithms and VLSI Architectures. Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2011.
Trouver le texte intégral1954-, Mayer-Kress G., et International Workshop on "Dimensions and Entropies in Chaotic Systems" (1985 : Pecos River Ranch), dir. Dimensions and entropies in chaotic systems : Quantification of complex behavior : proceedings of an international workshop at the Pecos River Ranch, New Mexico, September 11-16, 1985. Berlin : Springer-Verlag, 1986.
Trouver le texte intégralSbert, Mateu. Information theory tools for computer graphics. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, 2009.
Trouver le texte intégralUnited States. National Aeronautics and Space Administration., dir. An adaptive numeric predictor-corrector guidance algorithm for atmospheric entry vehicles. Cambridge, Mass : The Charles Stark Draper Laboratories, Inc., 1987.
Trouver le texte intégralUnited States. National Aeronautics and Space Administration., dir. Entry vehicle performance analysis and atmospheric guidance algorithm for precision landing on Mars. Cambridge, Mass : The Charles Stark Draper Laboratory, Inc., 1990.
Trouver le texte intégralChapitres de livres sur le sujet "Entropy algorithms"
Pham, Tuan D. « Entropy Algorithms ». Dans Fuzzy Recurrence Plots and Networks with Applications in Biomedicine, 81–97. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37530-0_6.
Texte intégralCardinal, Jean, Samuel Fiorini et Gwenaël Joret. « Minimum Entropy Coloring ». Dans Algorithms and Computation, 819–28. Berlin, Heidelberg : Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11602613_82.
Texte intégralMasters, Timothy. « Information and Entropy ». Dans Data Mining Algorithms in C++, 1–73. Berkeley, CA : Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3315-3_1.
Texte intégralLi, C. H., C. K. Lee et P. K. S. Tam. « Entropic Thresholding Algorithms and their Optimizations ». Dans Entropy Measures, Maximum Entropy Principle and Emerging Applications, 199–208. Berlin, Heidelberg : Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36212-8_10.
Texte intégralCordova, Joshimar, et Gonzalo Navarro. « Practical Dynamic Entropy-Compressed Bitvectors with Applications ». Dans Experimental Algorithms, 105–17. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38851-9_8.
Texte intégralFarzan, Arash, Travis Gagie et Gonzalo Navarro. « Entropy-Bounded Representation of Point Grids ». Dans Algorithms and Computation, 327–38. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17514-5_28.
Texte intégralFerragina, Paolo. « Data Structures : Time, I/Os, Entropy, Joules ! » Dans Algorithms – ESA 2010, 1–16. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15781-3_1.
Texte intégraldos Santos, Cícero Nogueira, et Ruy Luiz Milidiú. « Entropy Guided Transformation Learning ». Dans Entropy Guided Transformation Learning : Algorithms and Applications, 9–21. London : Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2978-3_2.
Texte intégralCooke, D. E., V. Kreinovich et L. Longpré. « Which Algorithms are Feasible ? Maxent Approach ». Dans Maximum Entropy and Bayesian Methods, 25–33. Dordrecht : Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5028-6_3.
Texte intégralShapiro, Jonathan L., Magnus Rattray et Adam PrüGel-Bennett. « Maximum Entropy Analysis of Genetic Algorithms ». Dans Maximum Entropy and Bayesian Methods, 303–10. Dordrecht : Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-5430-7_36.
Texte intégralActes de conférences sur le sujet "Entropy algorithms"
Feng, Xilong, Guosheng Hao, Yi Zhu et Shijin Ren. « An Entropy Feedback Based Evolutionary Algorithms and its Application ». Dans 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS), 685–95. IEEE, 2024. http://dx.doi.org/10.1109/docs63458.2024.10704514.
Texte intégralKurt, İlke, Sezer Ulukaya, Oğuzhan Erdem, Sibel Güler et Cem Uzun. « Shannon Wavelet Entropy-based Machine Learning Applications in Parkinson’s Disease Diagnosis with Videonystagmography ». Dans 2024 Signal Processing : Algorithms, Architectures, Arrangements, and Applications (SPA), 127–31. IEEE, 2024. http://dx.doi.org/10.23919/spa61993.2024.10715608.
Texte intégralAntoneac, Andrada-Livia, Gheorghiţă Mutu et Dragoş-Teodor Gavriluţ. « Entropy-Driven Visualization in GView : Unveiling the Unknown in Binary File Formats ». Dans 2024 26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 74–81. IEEE, 2024. https://doi.org/10.1109/synasc65383.2024.00025.
Texte intégralLan, Rui, Liang Gao et Chao Liu. « Research on the evaluation model of human job matching based on improved entropy method ». Dans Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), sous la direction de Qinghua Lu et Weishan Zhang, 3. SPIE, 2024. http://dx.doi.org/10.1117/12.3049482.
Texte intégralHarvey, Nicholas J. A., Jelani Nelson et Krzysztof Onak. « Streaming algorithms for estimating entropy ». Dans 2008 IEEE Information Theory Workshop (ITW). IEEE, 2008. http://dx.doi.org/10.1109/itw.2008.4578656.
Texte intégralSuciu, Alin, Kinga Marton et Zoltan Antal. « Data Flow Entropy Collector ». Dans 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. IEEE, 2008. http://dx.doi.org/10.1109/synasc.2008.25.
Texte intégralNadar, Mariappan S., Philip J. Sementilli et Bobby R. Hunt. « A Projection-Onto-Convex-Sets Interpretation of Cross-Entropy Based Image Super-Resolution Algorithms ». Dans Signal Recovery and Synthesis. Washington, D.C. : Optica Publishing Group, 1995. http://dx.doi.org/10.1364/srs.1995.rwc3.
Texte intégralRothvoß, Thomas. « The Entropy Rounding Method in Approximation Algorithms ». Dans Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA : Society for Industrial and Applied Mathematics, 2012. http://dx.doi.org/10.1137/1.9781611973099.32.
Texte intégralChang-Yong Lee. « Genetic algorithms with entropy-Boltzmann samplings ». Dans Proceedings of the 2001 Congress on Evolutionary Computation. IEEE, 2001. http://dx.doi.org/10.1109/cec.2001.934432.
Texte intégralWentao Ma, Hua Qu, Jihong Zhao, Badong Chen et Jose C. Principe. « Sparsity aware minimum error entropy algorithms ». Dans ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178357.
Texte intégralRapports d'organisations sur le sujet "Entropy algorithms"
Youssef, Abdou. Parallel algorithms for entropy-coding techniques. Gaithersburg, MD : National Institute of Standards and Technology, 1998. http://dx.doi.org/10.6028/nist.ir.6113.
Texte intégralDolotii, Marharyta H., et Pavlo V. Merzlykin. Using the random number generator with a hardware entropy source for symmetric cryptography problems. [б. в.], décembre 2018. http://dx.doi.org/10.31812/123456789/2883.
Texte intégralAlwan, Iktimal, Dennis D. Spencer et Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, décembre 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.
Texte intégralAllende López, Marcos, Diego López, Sergio Cerón, Antonio Leal, Adrián Pareja, Marcelo Da Silva, Alejandro Pardo et al. Quantum-Resistance in Blockchain Networks. Inter-American Development Bank, juin 2021. http://dx.doi.org/10.18235/0003313.
Texte intégralLiu, Ju, Hector Gomez, John A. Evans, Thomas J. Hughes et Chad M. Landis. Functional Entropy Variables : A New Methodology for Deriving Thermodynamically Consistent Algorithms for Complex Fluids, with Particular Reference to the Isothermal Navier-Stokes-Korteweg Equations. Fort Belvoir, VA : Defense Technical Information Center, novembre 2012. http://dx.doi.org/10.21236/ada572015.
Texte intégralFellman, Laura. The Genetic Algorithm and Maximum Entropy Dice. Portland State University Library, janvier 2000. http://dx.doi.org/10.15760/etd.7120.
Texte intégralSoloviev, Vladimir, Andrii Bielinskyi et Viktoria Solovieva. Entropy Analysis of Crisis Phenomena for DJIA Index. [б. в.], juin 2019. http://dx.doi.org/10.31812/123456789/3179.
Texte intégralBerney, Ernest, Naveen Ganesh, Andrew Ward, J. Newman et John Rushing. Methodology for remote assessment of pavement distresses from point cloud analysis. Engineer Research and Development Center (U.S.), avril 2021. http://dx.doi.org/10.21079/11681/40401.
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