Bibliografías temáticas / Principal component analysis / Artículos de revistas

Artículos de revistas sobre el tema "Principal component analysis"

Siga este enlace para ver otros tipos de publicaciones sobre el tema: Principal component analysis.
Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 8 de junio de 2024

Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros

Elija tipo de fuente:

Consulte los 50 mejores artículos de revistas para su investigación sobre el tema "Principal component analysis".

Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.

También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.

Explore artículos de revistas sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.

1

Barros, António S. y Douglas N. Rutledge. "Segmented principal component transform–principal component analysis". Chemometrics and Intelligent Laboratory Systems 78, n.º 1-2 (julio de 2005): 125–37. http://dx.doi.org/10.1016/j.chemolab.2005.01.003.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
2

Gewers, Felipe L., Gustavo R. Ferreira, Henrique F. De Arruda, Filipi N. Silva, Cesar H. Comin, Diego R. Amancio y Luciano Da F. Costa. "Principal Component Analysis". ACM Computing Surveys 54, n.º 4 (mayo de 2021): 1–34. http://dx.doi.org/10.1145/3447755.

Texto completo
Resumen
Principal component analysis (PCA) is often applied for analyzing data in the most diverse areas. This work reports, in an accessible and integrated manner, several theoretical and practical aspects of PCA. The basic principles underlying PCA, data standardization, possible visualizations of the PCA results, and outlier detection are subsequently addressed. Next, the potential of using PCA for dimensionality reduction is illustrated on several real-world datasets. Finally, we summarize PCA-related approaches and other dimensionality reduction techniques. All in all, the objective of this work is to assist researchers from the most diverse areas in using and interpreting PCA.
Los estilos APA, Harvard, Vancouver, ISO, etc.
3

Richards, Larry E. y I. T. Jolliffe. "Principal Component Analysis". Journal of Marketing Research 25, n.º 4 (noviembre de 1988): 410. http://dx.doi.org/10.2307/3172953.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
4

Lever, Jake, Martin Krzywinski y Naomi Altman. "Principal component analysis". Nature Methods 14, n.º 7 (julio de 2017): 641–42. http://dx.doi.org/10.1038/nmeth.4346.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
5

Timmerman, Marieke E. "Principal Component Analysis". Journal of the American Statistical Association 98, n.º 464 (diciembre de 2003): 1082–83. http://dx.doi.org/10.1198/jasa.2003.s308.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
6

Goodall, Colin. "Principal Component Analysis". Technometrics 30, n.º 3 (agosto de 1988): 351–52. http://dx.doi.org/10.1080/00401706.1988.10488412.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
7

Wold, Svante, Kim Esbensen y Paul Geladi. "Principal component analysis". Chemometrics and Intelligent Laboratory Systems 2, n.º 1-3 (agosto de 1987): 37–52. http://dx.doi.org/10.1016/0169-7439(87)80084-9.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
8

Law, John y I. T. Jolliffe. "Principal Component Analysis." Statistician 36, n.º 4 (1987): 432. http://dx.doi.org/10.2307/2348864.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
9

Hess, Aaron S. y John R. Hess. "Principal component analysis". Transfusion 58, n.º 7 (6 de mayo de 2018): 1580–82. http://dx.doi.org/10.1111/trf.14639.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
10

Bro, Rasmus y Age K. Smilde. "Principal component analysis". Anal. Methods 6, n.º 9 (2014): 2812–31. http://dx.doi.org/10.1039/c3ay41907j.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
11

Abdi, Hervé y Lynne J. Williams. "Principal component analysis". Wiley Interdisciplinary Reviews: Computational Statistics 2, n.º 4 (30 de junio de 2010): 433–59. http://dx.doi.org/10.1002/wics.101.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
12

Guo, Hao, Kurt J. Marfurt y Jianlei Liu. "Principal component spectral analysis". GEOPHYSICS 74, n.º 4 (julio de 2009): P35—P43. http://dx.doi.org/10.1190/1.3119264.

Texto completo
Resumen
Spectral decomposition methods help illuminate lateral changes in porosity and thin-bed thickness. For broadband data, an interpreter might generate 80 or more somewhat redundant amplitude and phase spectral components spanning the usable seismic bandwidth at [Formula: see text] intervals. Large numbers of components can overload not only the interpreter but also the display hardware. We have used principal component analysis to reduce the multiplicity of spectral data and enhance the most energetic trends inside the data. Each principal component spectrum is mathematically orthogonal to other spectra, with the importance of each spectrum being proportional to the size of its corresponding eigenvalue. Principal components are ideally suited to identify geologic features that give rise to anomalous moderate- to high-amplitude spectra. Unlike the input spectral magnitude and phase components, the principal component spectra are not direct indicators of bed thickness. By combining the variability of multiple components, principal component spectra highlight stratigraphic features that can be interpreted using a seismic geomorphology workflow. By mapping the three largest principal components using the three primary colors of red, green, and blue, we could represent more than 80% of the spectral variance with a single image. We have applied and validated this workflow using a broadband data volume containing channels draining an unconformity, which was acquired over the Central Basin Platform, Texas, U.S.A. Principal component analysis reveals a channel system with only a few output data volumes. The same process provides the interpreter with flexibility to remove any unwanted high-amplitude geologic trends or random noise from the original spectral components by eliminating those principal components that do not aid in delineation of prospective features with their interpretation during the reconstruction process.
Los estilos APA, Harvard, Vancouver, ISO, etc.
13

Jiang, Hansi. "Modularity Component Analysis versus Principal Component Analysis". American Journal of Applied Mathematics 4, n.º 2 (2016): 99. http://dx.doi.org/10.11648/j.ajam.20160402.15.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
14

Moller, R. y A. Konies. "Coupled Principal Component Analysis". IEEE Transactions on Neural Networks 15, n.º 1 (enero de 2004): 214–22. http://dx.doi.org/10.1109/tnn.2003.820439.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
15

Hu, Yu-Pin y Ruey S. Tsay. "Principal Volatility Component Analysis". Journal of Business & Economic Statistics 32, n.º 2 (3 de abril de 2014): 153–64. http://dx.doi.org/10.1080/07350015.2013.818006.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
16

Tipping, Michael E. y Christopher M. Bishop. "Probabilistic Principal Component Analysis". Journal of the Royal Statistical Society: Series B (Statistical Methodology) 61, n.º 3 (agosto de 1999): 611–22. http://dx.doi.org/10.1111/1467-9868.00196.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
17

Zou, Hui, Trevor Hastie y Robert Tibshirani. "Sparse Principal Component Analysis". Journal of Computational and Graphical Statistics 15, n.º 2 (junio de 2006): 265–86. http://dx.doi.org/10.1198/106186006x113430.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
18

Lloyd, Seth, Masoud Mohseni y Patrick Rebentrost. "Quantum principal component analysis". Nature Physics 10, n.º 9 (27 de julio de 2014): 631–33. http://dx.doi.org/10.1038/nphys3029.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
19

Kao, Yi-Hao y Benjamin Van Roy. "Directed Principal Component Analysis". Operations Research 62, n.º 4 (agosto de 2014): 957–72. http://dx.doi.org/10.1287/opre.2014.1290.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
20

Akinduko, A. A. y A. N. Gorban. "Multiscale principal component analysis". Journal of Physics: Conference Series 490 (11 de marzo de 2014): 012081. http://dx.doi.org/10.1088/1742-6596/490/1/012081.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
21

Jie Luo, Bo Hu, Xie-Ting Ling y Ruey-Wen Liu. "Principal independent component analysis". IEEE Transactions on Neural Networks 10, n.º 4 (julio de 1999): 912–17. http://dx.doi.org/10.1109/72.774259.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
22

Wiesel, A. y A. O. Hero. "Decomposable Principal Component Analysis". IEEE Transactions on Signal Processing 57, n.º 11 (noviembre de 2009): 4369–77. http://dx.doi.org/10.1109/tsp.2009.2025806.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
23

Gupta, Ajay y Adrian Barbu. "Parameterized principal component analysis". Pattern Recognition 78 (junio de 2018): 215–27. http://dx.doi.org/10.1016/j.patcog.2018.01.018.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
24

Li, TianJiang y Qiang Du. "Abstract principal component analysis". Science China Mathematics 56, n.º 12 (29 de agosto de 2013): 2783–98. http://dx.doi.org/10.1007/s11425-013-4715-9.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
25

Candès, Emmanuel J., Xiaodong Li, Yi Ma y John Wright. "Robust principal component analysis?" Journal of the ACM 58, n.º 3 (mayo de 2011): 1–37. http://dx.doi.org/10.1145/1970392.1970395.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
26

Liwicki, Stephan, Georgios Tzimiropoulos, Stefanos Zafeiriou y Maja Pantic. "Euler Principal Component Analysis". International Journal of Computer Vision 101, n.º 3 (5 de septiembre de 2012): 498–518. http://dx.doi.org/10.1007/s11263-012-0558-z.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
27

Fearn, Tom. "Probabilistic Principal Component Analysis". NIR news 25, n.º 3 (mayo de 2014): 23. http://dx.doi.org/10.1255/nirn.1439.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
28

Sando, Keishi y Hideitsu Hino. "Modal Principal Component Analysis". Neural Computation 32, n.º 10 (octubre de 2020): 1901–35. http://dx.doi.org/10.1162/neco_a_01308.

Texto completo
Resumen
Principal component analysis (PCA) is a widely used method for data processing, such as for dimension reduction and visualization. Standard PCA is known to be sensitive to outliers, and various robust PCA methods have been proposed. It has been shown that the robustness of many statistical methods can be improved using mode estimation instead of mean estimation, because mode estimation is not significantly affected by the presence of outliers. Thus, this study proposes a modal principal component analysis (MPCA), which is a robust PCA method based on mode estimation. The proposed method finds the minor component by estimating the mode of the projected data points. As a theoretical contribution, probabilistic convergence property, influence function, finite-sample breakdown point, and its lower bound for the proposed MPCA are derived. The experimental results show that the proposed method has advantages over conventional methods.
Los estilos APA, Harvard, Vancouver, ISO, etc.
29

Nounou, Mohamed N., Bhavik R. Bakshi, Prem K. Goel y Xiaotong Shen. "Bayesian principal component analysis". Journal of Chemometrics 16, n.º 11 (2002): 576–95. http://dx.doi.org/10.1002/cem.759.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
30

Aflalo, Yonathan y Ron Kimmel. "Regularized principal component analysis". Chinese Annals of Mathematics, Series B 38, n.º 1 (enero de 2017): 1–12. http://dx.doi.org/10.1007/s11401-016-1061-6.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
31

Saegusa, Ryo, Hitoshi Sakano y Shuji Hashimoto. "Nonlinear principal component analysis to preserve the order of principal components". Neurocomputing 61 (octubre de 2004): 57–70. http://dx.doi.org/10.1016/j.neucom.2004.03.004.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
32

Hassani, Sahar, Harald Martens, El Mostafa Qannari y Achim Kohler. "Degrees of freedom estimation in Principal Component Analysis and Consensus Principal Component Analysis". Chemometrics and Intelligent Laboratory Systems 118 (agosto de 2012): 246–59. http://dx.doi.org/10.1016/j.chemolab.2012.05.015.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
33

Li, Zhaokai, Zihua Chai, Yuhang Guo, Wentao Ji, Mengqi Wang, Fazhan Shi, Ya Wang, Seth Lloyd y Jiangfeng Du. "Resonant quantum principal component analysis". Science Advances 7, n.º 34 (agosto de 2021): eabg2589. http://dx.doi.org/10.1126/sciadv.abg2589.

Texto completo
Resumen
Principal component analysis (PCA) has been widely adopted to reduce the dimension of data while preserving the information. The quantum version of PCA (qPCA) can be used to analyze an unknown low-rank density matrix by rapidly revealing the principal components of it, i.e., the eigenvectors of the density matrix with the largest eigenvalues. However, because of the substantial resource requirement, its experimental implementation remains challenging. Here, we develop a resonant analysis algorithm with minimal resource for ancillary qubits, in which only one frequency-scanning probe qubit is required to extract the principal components. In the experiment, we demonstrate the distillation of the first principal component of a 4 × 4 density matrix, with an efficiency of 86.0% and a fidelity of 0.90. This work shows the speedup ability of quantum algorithm in dimension reduction of data and thus could be used as part of quantum artificial intelligence algorithms in the future.
Los estilos APA, Harvard, Vancouver, ISO, etc.
34

prakash, Mr S. Om y Gokila S. "Principal Component Analysis - A Survey". IJARCCE 7, n.º 8 (30 de agosto de 2018): 63–66. http://dx.doi.org/10.17148/ijarcce.2018.7814.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
35

McLean, Robert A. "Immunization Using Principal Component Analysis". CFA Digest 27, n.º 3 (agosto de 1997): 32–33. http://dx.doi.org/10.2469/dig.v27.n3.112.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
36

Chun, Young-Jae, Kyoung-Su Oh y Sung-Hyun Cho. "Photomosaics Using Principal Component Analysis". Journal of Korea Game Society 11, n.º 1 (28 de febrero de 2011): 139–46. http://dx.doi.org/10.7583/jkgs.2011.11.1.139.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
37

Adamu, Nuraddeen, Samaila Abdullahi y Sani Musa. "Online Stochastic Principal Component Analysis". Caliphate Journal of Science and Technology 4, n.º 1 (10 de febrero de 2022): 101–8. http://dx.doi.org/10.4314/cajost.v4i1.13.

Texto completo
Resumen
This paper studied Principal Component Analysis (PCA) in an online. The problem is posed as a subspace optimization problem and solved using gradient based algorithms. One such algorithm is the Variance-Reduced PCA (VR-PCA). The VR-PCA was designed as an improvement to the classical online PCA algorithm known as the Oja’s method where it only handled one sample at a time. The paper developed Block VR-PCA as an improved version of VR-PCA. Unlike prominent VR-PCA, the Block VR-PCA was designed to handle more than one dimension in subspace optimization at a time and it showed good performance. The Block VR-PCA and Block Oja method were compared experimentally in MATLAB using synthetic and real data sets, their convergence results showed Block VR-PCA method appeared to achieve a minimum steady state error than Block Oja method. Keywords: Online Stochastic; Principal Component Analysis; Block Variance-Reduced; Block Oja
Los estilos APA, Harvard, Vancouver, ISO, etc.
38

Everitt, B. S. y P. M. Kroonenberg. "Three-Mode Principal Component Analysis." Biometrics 42, n.º 1 (marzo de 1986): 224. http://dx.doi.org/10.2307/2531268.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
39

Barber, Joel R. y Mark L. Copper. "Immunization Using Principal Component Analysis". Journal of Portfolio Management 23, n.º 1 (31 de octubre de 1996): 99–105. http://dx.doi.org/10.3905/jpm.1996.409574.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
40

TAKANE, Yoshio. "ON CONSTRAINED PRINCIPAL COMPONENT ANALYSIS". Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 19, n.º 1 (1992): 29–39. http://dx.doi.org/10.2333/jbhmk.19.29.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
41

Gortler, Jochen, Thilo Spinner, Dirk Streeb, Daniel Weiskopf y Oliver Deussen. "Uncertainty-Aware Principal Component Analysis". IEEE Transactions on Visualization and Computer Graphics 26, n.º 1 (enero de 2020): 822–31. http://dx.doi.org/10.1109/tvcg.2019.2934812.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
42

Tharwat, Alaa. "Principal component analysis - a tutorial". International Journal of Applied Pattern Recognition 3, n.º 3 (2016): 197. http://dx.doi.org/10.1504/ijapr.2016.079733.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
43

Tharwat, Alaa. "Principal component analysis - a tutorial". International Journal of Applied Pattern Recognition 3, n.º 3 (2016): 197. http://dx.doi.org/10.1504/ijapr.2016.10000630.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
44

Vidal, R., Yi Ma y S. Sastry. "Generalized principal component analysis (GPCA)". IEEE Transactions on Pattern Analysis and Machine Intelligence 27, n.º 12 (diciembre de 2005): 1945–59. http://dx.doi.org/10.1109/tpami.2005.244.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
45

Shou, Haochang, Vadim Zipunnikov, Ciprian M. Crainiceanu y Sonja Greven. "Structured functional principal component analysis". Biometrics 71, n.º 1 (18 de octubre de 2014): 247–57. http://dx.doi.org/10.1111/biom.12236.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
46

Lin, Zhenhua, Liangliang Wang y Jiguo Cao. "Interpretable functional principal component analysis". Biometrics 72, n.º 3 (18 de diciembre de 2015): 846–54. http://dx.doi.org/10.1111/biom.12457.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
47

Sang, Peijun, Liangliang Wang y Jiguo Cao. "Parametric functional principal component analysis". Biometrics 73, n.º 3 (10 de marzo de 2017): 802–10. http://dx.doi.org/10.1111/biom.12641.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
48

Ibazizen, Mohamed y Jacques Dauxois. "A robust principal component analysis". Statistics 37, n.º 1 (enero de 2003): 73–83. http://dx.doi.org/10.1080/0233188031000065442.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
49

Richards, Larry E. "Book Review: Principal Component Analysis". Journal of Marketing Research 25, n.º 4 (noviembre de 1988): 410. http://dx.doi.org/10.1177/002224378802500410.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
50

Zhao, Zhizhen, Yoel Shkolnisky y Amit Singer. "Fast Steerable Principal Component Analysis". IEEE Transactions on Computational Imaging 2, n.º 1 (marzo de 2016): 1–12. http://dx.doi.org/10.1109/tci.2016.2514700.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
También puede estar interesado en las bibliografías sobre el tema "Principal component analysis" para otros tipos de fuentes:
Tesis Libros
Ofrecemos descuentos en todos los planes premium para autores cuyas obras están incluidas en selecciones literarias temáticas. ¡Contáctenos para obtener un código promocional único!

Pasar a la bibliografía