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Auswahl der wissenschaftlichen Literatur zum Thema „Disjoint component analysis“
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Zeitschriftenartikel zum Thema "Disjoint component analysis"
Ferrara, Carla, Francesca Martella und Maurizio Vichi. „Probabilistic Disjoint Principal Component Analysis“. Multivariate Behavioral Research 54, Nr. 1 (07.11.2018): 47–61. http://dx.doi.org/10.1080/00273171.2018.1485006.
Der volle Inhalt der QuelleVichi, Maurizio, und Gilbert Saporta. „Clustering and disjoint principal component analysis“. Computational Statistics & Data Analysis 53, Nr. 8 (Juni 2009): 3194–208. http://dx.doi.org/10.1016/j.csda.2008.05.028.
Der volle Inhalt der QuelleLamboy, Warren F. „Disjoint Principal Component Analysis: A Statistical Method of Botanical Identification“. Systematic Botany 15, Nr. 1 (Januar 1990): 3. http://dx.doi.org/10.2307/2419010.
Der volle Inhalt der QuelleHu, Qiguo, und Jinyin He. „Path Sets Combination Method for Reliability Analysis of Phased-Mission Systems Based on Cumulative Exposure Model“. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 36, Nr. 5 (Oktober 2018): 995–1003. http://dx.doi.org/10.1051/jnwpu/20183650995.
Der volle Inhalt der QuelleMartin-Barreiro, Carlos, John A. Ramirez-Figueroa, Xavier Cabezas, Víctor Leiva und M. Purificación Galindo-Villardón. „Disjoint and Functional Principal Component Analysis for Infected Cases and Deaths Due to COVID-19 in South American Countries with Sensor-Related Data“. Sensors 21, Nr. 12 (14.06.2021): 4094. http://dx.doi.org/10.3390/s21124094.
Der volle Inhalt der QuelleMeghanathan, Natarajan. „Quantifying the Theory Vs. Programming Disparity using Spectral Bipartivity Analysis and Principal Component Analysis“. International Journal of Computer Science and Information Technology 14, Nr. 5 (31.10.2022): 1–15. http://dx.doi.org/10.5121/ijcsit.2022.14501.
Der volle Inhalt der QuelleNose-Filho, Kenji, und Joao Marcos Travassos Romano. „Low-Rank Decomposition Based on Disjoint Component Analysis With Applications in Seismic Imaging“. IEEE Transactions on Computational Imaging 3, Nr. 2 (Juni 2017): 275–81. http://dx.doi.org/10.1109/tci.2017.2691548.
Der volle Inhalt der QuelleLONG, HAO, und XIAO-WEI LIU. „A UNIFIED COMMUNITY DETECTION ALGORITHM IN LARGE-SCALE COMPLEX NETWORKS“. Advances in Complex Systems 22, Nr. 03 (Mai 2019): 1950004. http://dx.doi.org/10.1142/s0219525919500048.
Der volle Inhalt der QuelleYu, Kong Shuai, und Dong Hu. „Appearance Model Based Moving Object Matching across Disjoint Camera Views“. Advanced Materials Research 760-762 (September 2013): 1322–26. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1322.
Der volle Inhalt der QuelleVesper, Stephen, Jennie Wakefield, Peter Ashley, David Cox, Gary Dewalt und Warren Friedman. „Geographic Distribution of Environmental Relative Moldiness Index Molds in USA Homes“. Journal of Environmental and Public Health 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/242457.
Der volle Inhalt der QuelleDissertationen zum Thema "Disjoint component analysis"
Zaghloul, Sara. „Application du DCA aux Radars de Surveillances Secondaires“. Electronic Thesis or Diss., Reims, 2024. http://www.theses.fr/2024REIMS017.
Der volle Inhalt der QuelleThe objective of this thesis was to develop a fast algorithm to separate a mixture of Secondary Surveillance Radar (SSR) signals. This mixture may include different modes, such as Mode A/C and Mode S, which complicate the separation due to their varied formats and different coding characteristics. During this thesis, three methods were developed using a relatively discrete criterion, the Disjoint Component Analysis (DCA), which aims to separate sources based on maximizing the disjointness between them.The first is a post-processing approach that uses linear algebra to solve the problems encountered when applying the real-valued version of DCA. However, the application of this method can pose several problems, including signal loss, residual mixing, and signal dependencies. Therefore, we concluded that it was necessary to develop a method that considers SSR signals in their original complex-valued format.The second method aims to demonstrate the effectiveness of the DCA criterion for SSR signals, using an exhaustive search approach while considering signals in their complex format. This method succeeds in separating signals with a high degree of accuracy but is computationally expensive.The third proposed method optimizes the search for the minimum using a gradient descent algorithm, which significantly improves computational efficiency while maintaining similar quality of results.These algorithms were tested in simulations and compared with various algorithms from the literature, to evaluate their performance as a function of different reception parameters. Finally, they were tested on real-world data
Buchteile zum Thema "Disjoint component analysis"
Nose-Filho, K., L. T. Duarte und J. M. T. Romano. „On Disjoint Component Analysis“. In Latent Variable Analysis and Signal Separation, 519–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53547-0_49.
Der volle Inhalt der QuelleAnemüller, Jörn, und Hendrik Kayser. „Acoustic Source Localization by Combination of Supervised Direction-of-Arrival Estimation with Disjoint Component Analysis“. In Latent Variable Analysis and Signal Separation, 99–108. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53547-0_10.
Der volle Inhalt der QuelleSekgweleo, Tefo, und Tiko Iyamu. „Human Interactions in Software Deployment“. In Advances in Human and Social Aspects of Technology, 161–78. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6126-4.ch009.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Disjoint component analysis"
Zaghloul, S., N. Petrochilos und M. Mboup. „Secondary Surveillance Radar replies source separation via the Disjoint Component Analysis“. In International Conference on Radar Systems (RADAR 2022). Institution of Engineering and Technology, 2022. http://dx.doi.org/10.1049/icp.2022.2365.
Der volle Inhalt der QuelleAkhonda, M. A. B. S., Qunfang Long, Suchita Bhinge, Vince D. Calhoun und Tulay Adali. „Disjoint Subspaces for Common and Distinct Component Analysis: Application to Task FMRI Data“. In 2019 53rd Annual Conference on Information Sciences and Systems (CISS). IEEE, 2019. http://dx.doi.org/10.1109/ciss.2019.8693045.
Der volle Inhalt der QuelleLagniez, Jean-Marie, und Pierre Marquis. „An Improved Decision-DNNF Compiler“. In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/93.
Der volle Inhalt der QuelleEnright, Michael P., R. Craig McClung, Kwai S. Chan, John McFarland, Jonathan P. Moody und James C. Sobotka. „Micromechanics-Based Fracture Risk Assessment Using Integrated Probabilistic Damage Tolerance Analysis and Manufacturing Process Models“. In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-58089.
Der volle Inhalt der QuelleKuczera, Ramon C., Zissimos P. Mourelatos und Michael Latcha. „A Monte Carlo Reliability Assessment for Multiple Failure Region Problems Using Approximate Metamodels“. In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-34957.
Der volle Inhalt der QuelleSlanjankic, Emir, Haris Balta, Adil Joldic, Alsa Cvitkovic, Djenan Heric und Emir Veledar. „Data mining techniques and SAS as a tool for graphical presentation of principal components analysis and disjoint cluster analysis results“. In 2009 XXII International Symposium on Information, Communication and Automation Technologies (ICAT 2009). IEEE, 2009. http://dx.doi.org/10.1109/icat.2009.5348419.
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