Literatura académica sobre el tema "PCA ALGORITHM"
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Artículos de revistas sobre el tema "PCA ALGORITHM"
Dinanti, Aldila y Joko Purwadi. "Analisis Performa Algoritma K-Nearest Neighbor dan Reduksi Dimensi Menggunakan Principal Component Analysis". Jambura Journal of Mathematics 5, n.º 1 (1 de febrero de 2023): 155–65. http://dx.doi.org/10.34312/jjom.v5i1.17098.
Texto completoSubramaniam, Ashwin y Byung-Joo Oh. "Mushroom Recognition Using PCA Algorithm". International Journal of Software Engineering and Its Applications 10, n.º 1 (31 de enero de 2016): 43–50. http://dx.doi.org/10.14257/ijseia.2016.10.1.05.
Texto completoSubiyanto, Subiyanto, Dina Priliyana, Moh Eki Riyadani, Nur Iksan y Hari Wibawanto. "Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi". Jurnal Teknologi dan Sistem Komputer 8, n.º 3 (25 de mayo de 2020): 210–16. http://dx.doi.org/10.14710/jtsiskom.2020.13590.
Texto completoZhang, Kang, Yongdong Huang y Cheng Zhao. "Remote sensing image fusion via RPCA and adaptive PCNN in NSST domain". International Journal of Wavelets, Multiresolution and Information Processing 16, n.º 05 (septiembre de 2018): 1850037. http://dx.doi.org/10.1142/s0219691318500376.
Texto completoHadiprakoso, Raden Budiarto y I. Komang Setia Buana. "Performance Comparison of Feature Extraction and Machine Learning Classification Algorithms for Face Recognition". IJICS (International Journal of Informatics and Computer Science) 5, n.º 3 (30 de noviembre de 2021): 250. http://dx.doi.org/10.30865/ijics.v5i3.3333.
Texto completoDolan, Matthew T., Sung Kim, Yu-Hsuan Shao y Grace L. Lu-Yao. "Authentication of Algorithm to Detect Metastases in Men with Prostate Cancer Using ICD-9 Codes". Epidemiology Research International 2012 (22 de agosto de 2012): 1–7. http://dx.doi.org/10.1155/2012/970406.
Texto completoZhao, Wenjing, Yue Chi, Yatong Zhou y Cheng Zhang. "Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation". Mathematical Problems in Engineering 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/1259703.
Texto completoLi, Mingfei, Zhengpeng Chen, Jiangbo Dong, Kai Xiong, Chuangting Chen, Mumin Rao, Zhiping Peng, Xi Li y Jingxuan Peng. "A Data-Driven Fault Diagnosis Method for Solid Oxide Fuel Cell Systems". Energies 15, n.º 7 (31 de marzo de 2022): 2556. http://dx.doi.org/10.3390/en15072556.
Texto completoVu, L. G., Abeer Alsadoon, P. W. C. Prasad y A. M. S. Rahma. "Improving Accuracy in Face Recognition Proposal to Create a Hybrid Photo Indexing Algorithm, Consisting of Principal Component Analysis and a Triangular Algorithm (PCAaTA)". International Journal of Pattern Recognition and Artificial Intelligence 31, n.º 01 (enero de 2017): 1756001. http://dx.doi.org/10.1142/s0218001417560018.
Texto completoMoghaddasi, Zahra, Hamid A. Jalab, Rafidah Md Noor y Saeed Aghabozorgi. "Improving RLRN Image Splicing Detection with the Use of PCA and Kernel PCA". Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/606570.
Texto completoTesis sobre el tema "PCA ALGORITHM"
Petters, Patrik. "Development of a Supervised Multivariate Statistical Algorithm for Enhanced Interpretability of Multiblock Analysis". Thesis, Linköpings universitet, Matematiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138112.
Texto completoErgin, Emre. "Investigation Of Music Algorithm Based And Wd-pca Method Based Electromagnetic Target Classification Techniques For Their Noise Performances". Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611218/index.pdf.
Texto completoRomualdo, Kamilla Vogas. "Problemas direto e inverso de processos de separação em leito móvel simulado mediante mecanismos cinéticos de adsorção". Universidade do Estado do Rio de Janeiro, 2012. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=6750.
Texto completoSeveral important industrial applications involving adsorption processes, citing as an example the product purification, separation of substances, pollution control and moisture among others. The growing interest in processes of purification of biomolecules is mainly due to the development of biotechnology and the demand of pharmaceutical and chemical products with high purity. The simulated moving bed (SMB) chromatography is a continuous process that has been applied to simulate the movement of the adsorbent bed, in a countercurrent to the movement of liquid through the periodic exchange of the positions of input and output currents, being operated so continuous, notwithstanding the purity of the outlet streams. This is the extract, rich in the more strongly adsorbed component, and the raffinate, rich in the more weakly adsorbed component, the method being particularly suited to binary separations. The aim of this thesis is to study and evaluate different approaches using stochastic optimization methods for the inverse problem of the phenomena involved in the separation process in LMS. We used discrete models with different approaches to mass transfer. With the benefit of using a large number of theoretical plates in a column of moderate length, in this process the separation increases as the solute flowing through the bed, i.e. as many times as molecules interact between the mobile phase and stationary phase thus achieving the equilibrium. The modeling and simulation verified in these approaches allowed the assessment and identification of the main characteristics of a separation unit LMS. The application under consideration refers to the simulation of the separation of Ketamine and Baclofen. These compounds were chosen because they are well characterized in the literature and are available in kinetic studies and equilibrium adsorption on experimental results. With the results of experiments evaluated the behavior of the direct and inverse problem of a separation unit LMS in order to compare these results, always based on the criteria of separation efficiency between the mobile and stationary phases. The methods studied were the GA (Genetic Algorithm) and PCA (Particle Collision Algorithm) and we also made a hybridization between the GA and PCA. This thesis, we analyzed and compared the optimization methods in different aspects of the kinetic mechanism for mass transfer between the adsorption and desorption of the adsorbent solid phases.
SINGH, BHUPINDER. "A HYBRID MSVM COVID-19 IMAGE CLASSIFICATION ENHANCED USING PARTICLE SWARM OPTIMIZATION". Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18864.
Texto completoWang, Xuechuan y n/a. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition". Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030619.162803.
Texto completoWang, Xuechuan. "Feature Extraction and Dimensionality Reduction in Pattern Recognition and Their Application in Speech Recognition". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365680.
Texto completoThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Microelectronic Engineering
Full Text
Rimal, Suraj. "POPULATION STRUCTURE INFERENCE USING PCA AND CLUSTERING ALGORITHMS". OpenSIUC, 2021. https://opensiuc.lib.siu.edu/theses/2860.
Texto completoKatadound, Sachin. "Face Recognition: Study and Comparison of PCA and EBGM Algorithms". TopSCHOLAR®, 2004. http://digitalcommons.wku.edu/theses/241.
Texto completoPerez, Gallardo Jorge Raúl. "Ecodesign of large-scale photovoltaic (PV) systems with multi-objective optimization and Life-Cycle Assessment (LCA)". Phd thesis, Toulouse, INPT, 2013. http://oatao.univ-toulouse.fr/10505/1/perez_gallardo_partie_1_sur_2.pdf.
Texto completoLacasse, Alexandre. "Bornes PAC-Bayes et algorithmes d'apprentissage". Thesis, Université Laval, 2010. http://www.theses.ulaval.ca/2010/27635/27635.pdf.
Texto completoThe main purpose of this thesis is the theoretical study and the design of learning algorithms returning majority-vote classifiers. In particular, we present a PAC-Bayes theorem allowing us to bound the variance of the Gibbs’ loss (not only its expectation). We deduce from this theorem a bound on the risk of a majority vote tighter than the famous bound based on the Gibbs’ risk. We also present a theorem that allows to bound the risk associated with general loss functions. From this theorem, we design learning algorithms building weighted majority vote classifiers minimizing a bound on the risk associated with the following loss functions : linear, quadratic and exponential. Also, we present algorithms based on the randomized majority vote. Some of these algorithms compare favorably with AdaBoost.
Libros sobre el tema "PCA ALGORITHM"
Karakatič, Sašo y Iztok Fister ml. Strojno učenje: S Pythonom do prvega klasifikatorja. University of Maribor Press, 2022. http://dx.doi.org/10.18690/um.feri.1.2022.
Texto completoCoates, Laura C., Arthur Kavanaugh y Christopher T. Ritchlin. Treatment algorithm and treat to target. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198737582.003.0032.
Texto completoFiedler, Klaus y Florian Kutzner. Pseudocontingencies. Editado por Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.14.
Texto completoCapps, Carlos H. Setup reduction in PCB assembly: A group technology application using Genetic Algorithms. 1997.
Buscar texto completoFragoulis, George E. y Iain B. McInnes. Small molecules in the treatment of psoriatic arthritis. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198737582.003.0031.
Texto completoPittenger, Arthur O. An Introduction to Quantum Computing Algorithms (Progress in Computer Science and Applied Logic (PCS)). Birkhäuser Boston, 2001.
Buscar texto completoPazzi, Annalisa. Applicazioni Di Grafi e Algoritmi Alla Fuga Di Pac-Man Dal Ghosts Team: Codice Completo in Linguaggio C. Independently Published, 2020.
Buscar texto completoAlJaroudi, Wael. Myocardial Perfusion Imaging Before and After Cardiac Revascularization. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199392094.003.0015.
Texto completoMichael, Blair, Walker George y Willey Stuart, eds. Financial Markets and Exchanges Law. 3a ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/law/9780198827528.001.0001.
Texto completoCapítulos de libros sobre el tema "PCA ALGORITHM"
Tao, Yang y Yuanzi He. "Improved PCA Face Recognition Algorithm". En Communications in Computer and Information Science, 602–11. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7981-3_44.
Texto completoVerboven, Sabine, Peter J. Rousseeuw y Mia Hubert. "An improved algorithm for robust PCA". En COMPSTAT, 481–86. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-642-57678-2_67.
Texto completoDing, Shifei, Weikuan Jia, Chunyang Su, Xinzheng Xu y Liwen Zhang. "PCA-Based Elman Neural Network Algorithm". En Advances in Computation and Intelligence, 315–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92137-0_35.
Texto completoSalgado, Paulo y Getúlio Igrejas. "A PCA-Fuzzy Clustering Algorithm for Contours Analysis". En Advances in Intelligent and Soft Computing, 305–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24001-0_28.
Texto completoZhang, Haigang, Yixin Yin, Sen Zhang y Changyin Sun. "An Improved ELM Algorithm Based on PCA Technique". En Proceedings in Adaptation, Learning and Optimization, 95–104. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14066-7_10.
Texto completoDraganov, Ivo, Roumen Kountchev y Veska Georgieva. "Medical Images Transform by Multistage PCA-Based Algorithm". En Advances in Intelligent Analysis of Medical Data and Decision Support Systems, 89–100. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00029-9_8.
Texto completoDas, Debasis y Rajiv Misra. "A Parallel AES Encryption Algorithm Based on PCA". En Advances in Parallel Distributed Computing, 238–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24037-9_23.
Texto completoWen, Shicheng, Shijin Yuan, Bin Mu y Hongyu Li. "Robust PCA-Based Genetic Algorithm for Solving CNOP". En Intelligent Computing Theories and Methodologies, 597–606. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22180-9_59.
Texto completoBabu, Mylam Chinnappan y Sangaralingam Pushpa. "Genetic Algorithm-Based PCA Classification for Imbalanced Dataset". En Intelligent Computing in Engineering, 541–52. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2780-7_59.
Texto completoChang, W. H. y M. C. Cheng. "Image Retrieval by Auto Weight Regulation PCA Algorithm". En Intelligent Systems Design and Applications, 383–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44999-7_37.
Texto completoActas de conferencias sobre el tema "PCA ALGORITHM"
Dagher, Issam. "Incremental PCA-LDA algorithm". En 2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA). IEEE, 2010. http://dx.doi.org/10.1109/cimsa.2010.5611752.
Texto completoSalgado, Paulo, Lio Gonçalves, Getúlio Igrejas, Theodore E. Simos, George Psihoyios, Ch Tsitouras y Zacharias Anastassi. "Sliding PCA Fuzzy Clustering Algorithm". En NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3637005.
Texto completoFeng, Xu y Wenjian Yu. "A Fast Adaptive Randomized PCA Algorithm". En Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/411.
Texto completoHasanbelliu, Erion, Luis Sanchez Giraldo y Jose C. Principe. "A Recursive Online Kernel PCA Algorithm". En 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.50.
Texto completoWang, Qianqian, Quanxue Gao, Xinbo Gao y Feiping Nie. "Angle Principal Component Analysis". En Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/409.
Texto completoBansal, Abhishek, Kapil Mehta y Sahil Arora. "Face Recognition Using PCA and LDA Algorithm". En Communication Technologies (ACCT). IEEE, 2012. http://dx.doi.org/10.1109/acct.2012.52.
Texto completoLi, H. L., W. Quan, G. Ji y Z. H. Qian. "Wireless Indoor Positioning Algorithm Based on PCA". En 2015 International Conference on Artificial Intelligence and Industrial Engineering. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/aiie-15.2015.3.
Texto completoMelikyan, Vazgen y Hasmik Osipyan. "Modified fast PCA algorithm on GPU architecture". En 2014 East-West Design & Test Symposium (EWDTS). IEEE, 2014. http://dx.doi.org/10.1109/ewdts.2014.7027099.
Texto completoFengxiang Jin y Shifei Ding. "An improved PCA algorithm based on WIF". En 2008 IEEE International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong). IEEE, 2008. http://dx.doi.org/10.1109/ijcnn.2008.4634006.
Texto completoLi, Yuan-long, Jun Zhang y Wei-neng Chen. "Differential evolution algorithm with PCA-based crossover". En the fourteenth international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2330784.2331018.
Texto completoInformes sobre el tema "PCA ALGORITHM"
Zhao, George, Grang Mei, Bulent Ayhan, Chiman Kwan y Venu Varma. DTRS57-04-C-10053 Wave Electromagnetic Acoustic Transducer for ILI of Pipelines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), marzo de 2005. http://dx.doi.org/10.55274/r0012049.
Texto completoPoovendran, Radha y Brian Matt. Security Analysis and Extensions of the PCB Algorithm for Distributed Key Generation. Fort Belvoir, VA: Defense Technical Information Center, enero de 2005. http://dx.doi.org/10.21236/ada459087.
Texto completoSearcy, Stephen W. y Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, agosto de 1993. http://dx.doi.org/10.32747/1993.7568747.bard.
Texto completoPanek. PR-312-12208-R01 Plume Volume Molar Ratio Method Assumptions and Conservative Model Over-Predictions. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), abril de 2013. http://dx.doi.org/10.55274/r0010806.
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