Literatura académica sobre el tema "Adaptive snapshots"
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Artículos de revistas sobre el tema "Adaptive snapshots"
YU, Jing y Yaan LI. "Adaptive Beamforming with Inadequate Snapshots". Journal of Physics: Conference Series 787 (enero de 2017): 012025. http://dx.doi.org/10.1088/1742-6596/787/1/012025.
Texto completoLiao, Zhipeng, Keqing Duan, Jinjun He, Zizhou Qiu y Binbin Li. "Robust Adaptive Beamforming Based on a Convolutional Neural Network". Electronics 12, n.º 12 (20 de junio de 2023): 2751. http://dx.doi.org/10.3390/electronics12122751.
Texto completoWu, Xun, Jie Luo, Guowei Li, Shurui Zhang y Weixing Sheng. "Fast Wideband Beamforming Using Convolutional Neural Network". Remote Sensing 15, n.º 3 (25 de enero de 2023): 712. http://dx.doi.org/10.3390/rs15030712.
Texto completoGong, C., L. Huang, D. Xu y Z. Ye. "Knowledge‐aided robust adaptive beamforming with small snapshots". Electronics Letters 49, n.º 20 (septiembre de 2013): 1258–59. http://dx.doi.org/10.1049/el.2013.2198.
Texto completoBrooker, D. J., Kay L. Gemba y Laurie T. Fialkowski. "Overcoming snapshot-deficient measurements with knowledge-aided approaches". JASA Express Letters 2, n.º 5 (mayo de 2022): 054804. http://dx.doi.org/10.1121/10.0010455.
Texto completoSun, Xu y Ranwei Li. "Robust adaptive beamforming method for active sonar in single snapshot". MATEC Web of Conferences 283 (2019): 03006. http://dx.doi.org/10.1051/matecconf/201928303006.
Texto completoWang, He, Ting Zhang, Lei Cheng y Hangfang Zhao. "Snapshot-deficient active target localization in beam-time domain using multi-frequency expectation-maximization algorithm". Journal of the Acoustical Society of America 153, n.º 2 (febrero de 2023): 990–1003. http://dx.doi.org/10.1121/10.0017164.
Texto completoUllmann, Sebastian, Marko Rotkvic y Jens Lang. "POD-Galerkin reduced-order modeling with adaptive finite element snapshots". Journal of Computational Physics 325 (noviembre de 2016): 244–58. http://dx.doi.org/10.1016/j.jcp.2016.08.018.
Texto completoLi, Hongtao, Ke Wang, Chaoyu Wang, Yapeng He y Xiaohua Zhu. "Robust Adaptive Beamforming Based on Worst-Case and Norm Constraint". International Journal of Antennas and Propagation 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/765385.
Texto completoCui, Weichen, Tong Wang, Degen Wang y Kun Liu. "An Efficient Sparse Bayesian Learning STAP Algorithm with Adaptive Laplace Prior". Remote Sensing 14, n.º 15 (22 de julio de 2022): 3520. http://dx.doi.org/10.3390/rs14153520.
Texto completoTesis sobre el tema "Adaptive snapshots"
Chetry, Manisha. "Advanced reduced-order modeling and parametric sampling for non-Newtonian fluid flows". Electronic Thesis or Diss., Ecole centrale de Nantes, 2023. http://www.theses.fr/2023ECDN0011.
Texto completoThe subject of this thesis concernsmodel-order reduction (MOR) of parameterizednon-Newtonian flow problems that havesignificant industrial applications. TraditionalMOR methods constrain the computationalperformance of such highly nonlinear problems,so we suggest a state-of-the-art hyper-reductiontechnique based on a sparse approximation totackle the evaluation of nonlinear terms at muchreduced complexity. We also provide offlinestabilization strategy for stabilizing theconstitutive model in the reduced order modelframework that is less expensive to computewhile maintaining the full order model's (FOM)accuracy. Combining the two significantlylowers the CPU cost as compared to the FOMevaluation which inevitably boosts MORperformance. This work is validated on twobenchmark flow problems. Additionally, anadaptive sampling strategy is also presented inthis manuscript which is achieved byleveraging multi-fidelity model approximation.Towards the end of the thesis, we addressanother issue that is typically observed forcases when adaptive finite element meshesare deployed. In such cases, MOR methods failto produce a low-dimensional representationsince the snapshots are not vectors of samelength. We therefore, suggest an alternatemethod that can generate reduced basisfunctions for database of space-adaptedsnapshots
Kraay, Andrea L. (Andrea Lorraine) 1976. "Physically constrained maximum likelihood method for snapshot deficient adaptive array processing". Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87331.
Texto completo"February 2003."
Includes bibliographical references (leaves 139-141).
by Andrea L. Kraay.
Elec.E.and S.M.in Electrical Engineering
Minet, Jean. "Imagerie multispectrale, vers une conception adaptée à la détection de cibles". Phd thesis, Université Paris Sud - Paris XI, 2011. http://pastel.archives-ouvertes.fr/pastel-00714207.
Texto completoLibros sobre el tema "Adaptive snapshots"
Holland, John H. 4. Agents, networks, degree, and recirculation. Oxford University Press, 2014. http://dx.doi.org/10.1093/actrade/9780199662548.003.0004.
Texto completoClodfelter, Richard. Retail Buying. 7a ed. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9781501375651.
Texto completoCapítulos de libros sobre el tema "Adaptive snapshots"
Kastian, Steffen y Stefanie Reese. "An Adaptive Way of Choosing Significant Snapshots for Proper Orthogonal Decomposition". En IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018, 67–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21013-7_5.
Texto completoScherer, Cordula y Agnese Cretella. "Sustainable Seafood Consumption: A Matter of Individual Choice or Global Market? A Window into Dublin’s Seafood Scene". En Ocean Governance, 233–51. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-20740-2_10.
Texto completo"Direct Data Domain Least Squares Approaches to Adaptive Processing Based on Single Snapshots of Data". En Smart Antennas, 75–102. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471722839.ch4.
Texto completoCostello, Robert. "Supporting the Needs of the Independent Learner Within Higher Education". En Strategic Collaborative Innovations in Organizational Systems, 140–59. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7390-6.ch007.
Texto completoZhao, Y. "Ontology Mapping Techniques in Information Integration". En Adaptive Technologies and Business Integration, 308–28. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-048-6.ch015.
Texto completoChristopher, Spencer. "Life-Span Changes in Activities, and Consequent Changes in the Cognition and Assessment of the Environment". En Environment, Cognition, and Action. Oxford University Press, 1992. http://dx.doi.org/10.1093/oso/9780195062205.003.0021.
Texto completoZappalaglio, Andrea. "Sui generis, bureaucratic and based on origin: a snapshot of the nature of EU Geographical Indications". En Intellectual Property as a Complex Adaptive System, 132–52. Edward Elgar Publishing, 2021. http://dx.doi.org/10.4337/9781800378384.00018.
Texto completo"Direction of Arrival Estimation and Adaptive Processing Using a Nonuniformly Spaced Array from a Single Snapshot". En Smart Antennas, 147–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471722839.ch6.
Texto completoHeltzel, Lisa y Judith R. Homberg. "Animal models of post-traumatic stress disorder". En Genes, brain, and emotions, 324–42. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198793014.003.0022.
Texto completoActas de conferencias sobre el tema "Adaptive snapshots"
Geretto, Elia, Cristiano Giuffrida, Herbert Bos y Erik Van Der Kouwe. "Snappy: Efficient Fuzzing with Adaptive and Mutable Snapshots". En ACSAC: Annual Computer Security Applications Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3564625.3564639.
Texto completoZaharov, Viktor V. y Marvi Teixeira. "Adaptive Digital Non-Blind Beamformer for Small Number of Snapshots". En 2006 49th IEEE International Midwest Symposium on Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/mwscas.2006.382058.
Texto completoPan, Yundeng, Paul Liu y Dong Liu. "Adaptive Multiple Snapshots with Matrix Pencil Method for Color Flow Imaging". En 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2009). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5162279.
Texto completoMueller, C. y J. Lang. "A POD-Galerkin Model for Convection-Diffusion-Reaction Equations with Parametric Data based on Adaptive Snapshots". En XI International Conference on Adaptive Modeling and Simulation. CIMNE, 2023. http://dx.doi.org/10.23967/admos.2023.006.
Texto completoWeng, Junjie, Jun Liu y Siyu Sun. "DOA Estimation with Few Snapshots Based on Iterative Adaptive Approach and Eigenvalue Decomposition". En 2022 IEEE 22nd International Conference on Communication Technology (ICCT). IEEE, 2022. http://dx.doi.org/10.1109/icct56141.2022.10073164.
Texto completoGu, Yujie y Yimin D. Zhang. "Single-Snapshot Adaptive Beamforming". En 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2018. http://dx.doi.org/10.1109/sam.2018.8448680.
Texto completoAfek, Yehuda, Gideon Stupp y Dan Touitou. "Long-lived and adaptive atomic snapshot and immediate snapshot (extended abstract)". En the nineteenth annual ACM symposium. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/343477.343521.
Texto completoBrodie, C. Harrison y Christopher M. Collier. "Spatial light modulation and optical mixing for snapshot hyperspectral imaging architectures". En Unconventional Imaging and Adaptive Optics 2021, editado por Jean J. Dolne y Mark F. Spencer. SPIE, 2021. http://dx.doi.org/10.1117/12.2594261.
Texto completoBashari, Benyamin y Philipp Woelfel. "An Efficient Adaptive Partial Snapshot Implementation". En PODC '21: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3465084.3467939.
Texto completoHassanien, Aboulnasr y Elias Aboutanios. "Single-Snapshot Beamforming using Fast Iterative Adaptive Techniques". En 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2020. http://dx.doi.org/10.1109/sam48682.2020.9104350.
Texto completoInformes sobre el tema "Adaptive snapshots"
Oxberry, Geoffrey M., Tanya Kostova-Vassilevska, Bill Arrighi y Kyle Chand. Limited-memory adaptive snapshot selection for proper orthogonal decomposition. Office of Scientific and Technical Information (OSTI), abril de 2015. http://dx.doi.org/10.2172/1224940.
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