Literatura científica selecionada sobre o tema "SDP optimization"
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Artigos de revistas sobre o assunto "SDP optimization"
MEVISSEN, MARTIN, e MASAKAZU KOJIMA. "SDP RELAXATIONS FOR QUADRATIC OPTIMIZATION PROBLEMS DERIVED FROM POLYNOMIAL OPTIMIZATION PROBLEMS". Asia-Pacific Journal of Operational Research 27, n.º 01 (fevereiro de 2010): 15–38. http://dx.doi.org/10.1142/s0217595910002533.
Texto completo da fonteLiu, Yiyuan, Baoguo Li e Yizhou Yao. "Radar-Embedded Communication Waveform Design Based on Parameter Optimization". Journal of Physics: Conference Series 2404, n.º 1 (1 de dezembro de 2022): 012032. http://dx.doi.org/10.1088/1742-6596/2404/1/012032.
Texto completo da fonteMetzlaff, Tobias. "Symmetry Adapted Bases for Trigonometric Optimization". ACM Communications in Computer Algebra 57, n.º 3 (setembro de 2023): 137–40. http://dx.doi.org/10.1145/3637529.3637535.
Texto completo da fonteHu, En-Liang, e Bo Wang. "A new optimization in SDP-based learning". Neurocomputing 365 (novembro de 2019): 10–20. http://dx.doi.org/10.1016/j.neucom.2019.06.058.
Texto completo da fonteHu, Haijiang, Shaojing Song e Fengdeng Zhang. "FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization". Journal of Electrical and Computer Engineering 2020 (20 de fevereiro de 2020): 1–7. http://dx.doi.org/10.1155/2020/4503706.
Texto completo da fonteKANNO, Y., M. OHSAKI e N. KATOH. "SEQUENTIAL SEMIDEFINITE PROGRAMMING FOR OPTIMIZATION OF FRAMED STRUCTURES UNDER MULTIMODAL BUCKLING CONSTRAINTS". International Journal of Structural Stability and Dynamics 01, n.º 04 (dezembro de 2001): 585–602. http://dx.doi.org/10.1142/s0219455401000305.
Texto completo da fonteGil-González, Walter, Alexander Molina-Cabrera, Oscar Danilo Montoya e Luis Fernando Grisales-Noreña. "An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum". Applied Sciences 10, n.º 21 (30 de outubro de 2020): 7681. http://dx.doi.org/10.3390/app10217681.
Texto completo da fonteRen, Fangyu, Huotao Gao, Lijuan Yang e Sang Zhou. "Distributed Multistatic Sky-Wave Over-the-Horizon Radar’s Positioning Algorithm for the Marine Target". International Journal of Antennas and Propagation 2021 (27 de outubro de 2021): 1–7. http://dx.doi.org/10.1155/2021/1028784.
Texto completo da fonteNandyala, Raja Thejaswini, e Muthupandi Gandhi. "High uncertainty aware localization and error optimization of mobile nodes for wireless sensor networks". IAES International Journal of Artificial Intelligence (IJ-AI) 12, n.º 4 (1 de dezembro de 2023): 2022. http://dx.doi.org/10.11591/ijai.v12.i4.pp2022-2032.
Texto completo da fonteGuolei, Tang, Zhou Huicheng e Li Ningning. "Reservoir optimization model incorporating inflow forecasts with various lead times as hydrologic state variables". Journal of Hydroinformatics 12, n.º 3 (24 de novembro de 2009): 292–302. http://dx.doi.org/10.2166/hydro.2009.088.
Texto completo da fonteTeses / dissertações sobre o assunto "SDP optimization"
Campos, Salazar Juan. "A multigrid approach to SDP relaxations of sparse polynomial optimization problems". Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/56630.
Texto completo da fonteKhan, Ejaz. "Techniques itératives pour les systèmes CDMA et algorithmes de détection MIMO". Paris, ENST, 2003. http://www.theses.fr/2003ENST0020.
Texto completo da fonteWe focus on low complexity maximum likelihood detection. The em algorithm is a broadly applicable approach to the iterative computation of ml estimates, useful in variety of incomplete-data problems, where algorithms such as the newton-raphson method may turn out to be more complicated. In the first part of the thesis, we use em algorithm to estimate the channel amplitudes blindly and compare the results with the cramer-rao bound (crb). The second part of the thesis concerns the detection problem in mimo systems. We are able to device an algorithm for approximate ml detection using a discrete geometric approach. The advantage of this algorithm is that its performance is polynomial irrespective of the snr and no heuristic is employed in our algorithm. An alternative way to ml problem is to devise low complexity algorithms whose performance is close to the exact ml. This can be done using semidefinite programming (sdp) approach. The computational complexity of the sdp approach is comparable to the average complexity of the sphere decoder but still it is quite complicated for large systems. We obtained low complexity (by reducing the number of the variables) approximate ml by second order cone programming (socp) approach. In the above discussion the channel state information is assumed to be known at the receiver. We further looked into the problem of detection with no channel knowledge at the receiver. The result was the joint channel-symbol estimation. We obtained the results of joint channel-symbol estimation using em algorithm and in order to reduce the complexity of the resulting em algorithm, we used mean field theory (mft) approach
Passuello, Alberto. "Semidefinite programming in combinatorial optimization with applications to coding theory and geometry". Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00948055.
Texto completo da fonteNiu, Yi Shuai. "Programmation DC et DCA en optimisation combinatoire et optimisation polynomiale via les techniques de SDP : codes et simulations numériques". Phd thesis, INSA de Rouen, 2010. http://tel.archives-ouvertes.fr/tel-00557911.
Texto completo da fonteFraticelli, Barbara M. P. "Semidefinite Cuts and Partial Convexification Techniques with Applications to Continuous Nonconvex Optimization, Stochastic Integer Programming, and Facility Layout Problems". Diss., Virginia Tech, 2001. http://hdl.handle.net/10919/27293.
Texto completo da fontePh. D.
Fletcher, Thomas P. "Optimal energy management strategy for a fuel cell hybrid electric vehicle". Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/25567.
Texto completo da fonteHalalchi, Houssem. "Commande linéaire à paramètres variants des robots manipulateurs flexibles". Phd thesis, Université de Strasbourg, 2012. http://tel.archives-ouvertes.fr/tel-00762367.
Texto completo da fonteMonori, Akos. "Task assignment optimization in SAP Extended WarehouseManagement". Thesis, Högskolan Dalarna, Datateknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3598.
Texto completo da fonteGul, Sufi Tabassum. "Optimization of Multi-standards Software Defined Radio Equipments: A Common Operators Approach". Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00446230.
Texto completo da fonteMathews, Steffy Ann. "Optimization of an SDR Based Aerial Base Station". Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011834/.
Texto completo da fonteLivros sobre o assunto "SDP optimization"
SAP performance optimization guide. 6a ed. Bonn: Galileo Press, 2011.
Encontre o texto completo da fonteSAP performance optimization guide: Analyzing and tuning SAP systems. 7a ed. Bonn: Galileo Press, 2013.
Encontre o texto completo da fonteSAP R/3 performance optimization: The official SAP guide. San Francisco: Sybex, 1999.
Encontre o texto completo da fonteChristensen, Jesper. SAP BW: Administration and performance optimization. Bonn: Galileo Press, 2014.
Encontre o texto completo da fonteCorporation, International Business Machines, ed. DB2 optimization techniques for SAP database migration and Unicode conversion. [Poughkeepsie, N.Y.?]: IBM Corporation, International Technical Support Organization, 2009.
Encontre o texto completo da fonteservice), SpringerLink (Online, ed. Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE. New York, NY: Springer New York, 2013.
Encontre o texto completo da fonteNeureither, A. SAP System Landscape Optimization. SAP press, 2004.
Encontre o texto completo da fonteSAP Performance Optimization Guide. SAP Press, 2002.
Encontre o texto completo da fonteInventory Optimization with SAP. Rheinwerk Publishing Inc., 2009.
Encontre o texto completo da fonteSAP Performance Optimization Guide. 3a ed. SAP Press, 2003.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "SDP optimization"
Luo, Zhi-Quan, Jos F. Sturm e Shuzhong Zhang. "Superlinear Convergence of a Symmetric Primal-Dual Path Following Algorithm for SDP". In Applied Optimization, 283–97. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-3335-7_14.
Texto completo da fonteShamsi, Davood, Nicole Taheri, Zhisu Zhu e Yinyu Ye. "Conditions for Correct Sensor Network Localization Using SDP Relaxation". In Discrete Geometry and Optimization, 279–301. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00200-2_16.
Texto completo da fonteNavascués, Miguel, Stefano Pironio e Antonio Acín. "SDP Relaxations for Non-Commutative Polynomial Optimization". In Handbook on Semidefinite, Conic and Polynomial Optimization, 601–34. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_21.
Texto completo da fonteSotirov, Renata. "SDP Relaxations for Some Combinatorial Optimization Problems". In Handbook on Semidefinite, Conic and Polynomial Optimization, 795–819. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_27.
Texto completo da fonteLemaréchal, Claude, e François Oustry. "SDP Relaxations in Combinatorial Optimization from a Lagrangian Viewpoint". In Nonconvex Optimization and Its Applications, 119–34. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4613-0279-7_6.
Texto completo da fonteLasserre, Jean B. "Convergent SDP-Relaxations for Polynomial Optimization with Sparsity". In Lecture Notes in Computer Science, 263–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11832225_27.
Texto completo da fonteElbassioni, Khaled, e Kazuhisa Makino. "Oracle-Based Primal-Dual Algorithms for Packing and Covering Semidefinite Programs". In Sublinear Computation Paradigm, 47–63. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4095-7_4.
Texto completo da fonteLasserre, Jean B. "An Explicit Exact SDP Relaxation for Nonlinear 0-1 Programs". In Integer Programming and Combinatorial Optimization, 293–303. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45535-3_23.
Texto completo da fonteKim, Sunyoung, e Masakazu Kojima. "Exploiting Sparsity in SDP Relaxation of Polynomial Optimization Problems". In Handbook on Semidefinite, Conic and Polynomial Optimization, 499–531. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-0769-0_18.
Texto completo da fonteHsieh, Jun-Ting, Pravesh K. Kothari, Lucas Pesenti e Luca Trevisan. "New SDP Roundings and Certifiable Approximation for Cubic Optimization". In Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2337–62. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2024. http://dx.doi.org/10.1137/1.9781611977912.83.
Texto completo da fonteTrabalhos de conferências sobre o assunto "SDP optimization"
White, Jules, e Douglas C. Schmidt. "R&D challenges and emerging solutions for multicore deployment/configuration optimization". In the FSE/SDP workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1882362.1882445.
Texto completo da fonteSanmugadas, Varakini, e Rakesh K. Kapania. "Truss Topology Optimization With Semidefinite Programming and Parametric Model Order Reduction". In ASME 2023 Aerospace Structures, Structural Dynamics, and Materials Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/ssdm2023-108410.
Texto completo da fonteLee, Soomin, e Michael M. Zavlanos. "Approximate projections for decentralized optimization with SDP constraints". In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798403.
Texto completo da fonteWu, Liangting, e Roberto Tron. "An SDP Optimization Formulation for the Inverse Kinematics Problem". In 2023 62nd IEEE Conference on Decision and Control (CDC). IEEE, 2023. http://dx.doi.org/10.1109/cdc49753.2023.10384035.
Texto completo da fonteZhang, Qinghong, Gang Chen e Ting Zhang. "Self-Dual Embedding for SDP Using ELSD and its Lagrangian Dual". In 2010 Third International Joint Conference on Computational Science and Optimization. IEEE, 2010. http://dx.doi.org/10.1109/cso.2010.139.
Texto completo da fonteKrechetov, Mikhail, Jakub Marecek, Yury Maximov e Martin Takac. "Entropy-Penalized Semidefinite Programming". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/157.
Texto completo da fonteAlsaleh, Ibrahim, Lingling Fan e Minyue Ma. "Mixed-Integer SDP Relaxation-based Volt/Var Optimization for Unbalanced Distribution Systems". In 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019. http://dx.doi.org/10.1109/pesgm40551.2019.8973879.
Texto completo da fonteTomasin, Stefano, e Tomaso Erseghe. "Constrained optimization of local sources generation in smart grids by SDP approximation". In 2011 IEEE International Symposium on Power Line Communications and Its Applications (ISPLC). IEEE, 2011. http://dx.doi.org/10.1109/isplc.2011.5764388.
Texto completo da fonteAllen-Zhu, Zeyuan, Yin Tat Lee e Lorenzo Orecchia. "Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver". In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2015. http://dx.doi.org/10.1137/1.9781611974331.ch127.
Texto completo da fonteRapoport, Lev, e Timofey Tormagov. "Using of the SDP Relaxation Method for Optimization of the Satellites Set Chosen for Positioning". In 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018). Institute of Navigation, 2018. http://dx.doi.org/10.33012/2018.15994.
Texto completo da fonteRelatórios de organizações sobre o assunto "SDP optimization"
Alwan, Iktimal, Dennis D. Spencer e Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, dezembro de 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.
Texto completo da fonteOblow, E. M. STP: A Stochastic Tunneling Algorithm for Global Optimization. Office of Scientific and Technical Information (OSTI), maio de 1999. http://dx.doi.org/10.2172/814395.
Texto completo da fonteOron, Gideon, Raphi Mandelbaum, Carlos E. Enriquez, Robert Armon, Yoseph Manor, L. Gillerman, A. Alum e Charles P. Gerba. Optimization of Secondary Wastewater Reuse to Minimize Environmental Risks. United States Department of Agriculture, dezembro de 1999. http://dx.doi.org/10.32747/1999.7573077.bard.
Texto completo da fonteKing, Wayne. Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, maio de 2023. http://dx.doi.org/10.4271/epr2023011.
Texto completo da fonteKolodziejczyk, Bart. Emergence of Quantum Computing Technologies in Automotive Applications: Opportunities and Future Use Cases. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, abril de 2024. http://dx.doi.org/10.4271/epr2024008.
Texto completo da fonteBleuel, D. L., e R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), fevereiro de 1996. http://dx.doi.org/10.2172/212700.
Texto completo da fonteBleuel, B. L., e R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), maio de 1996. http://dx.doi.org/10.2172/273022.
Texto completo da fonteHeinkenschloss, Matthias, Denis Ridzal e Miguel Antonio Aguilo. Numerical study of a matrix-free trust-region SQP method for equality constrained optimization. Office of Scientific and Technical Information (OSTI), dezembro de 2011. http://dx.doi.org/10.2172/1038211.
Texto completo da fonteKhan, Samir. Towards MRO 4.0: Challenges for Digitalization and Mapping Emerging Technologies. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, abril de 2023. http://dx.doi.org/10.4271/epr2023007.
Texto completo da fonteWeller, Joel I., Ignacy Misztal e Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, março de 2015. http://dx.doi.org/10.32747/2015.7594404.bard.
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