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Auswahl der wissenschaftlichen Literatur zum Thema „SDP optimization“
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Zeitschriftenartikel zum Thema "SDP optimization"
MEVISSEN, MARTIN, und MASAKAZU KOJIMA. „SDP RELAXATIONS FOR QUADRATIC OPTIMIZATION PROBLEMS DERIVED FROM POLYNOMIAL OPTIMIZATION PROBLEMS“. Asia-Pacific Journal of Operational Research 27, Nr. 01 (Februar 2010): 15–38. http://dx.doi.org/10.1142/s0217595910002533.
Der volle Inhalt der QuelleLiu, Yiyuan, Baoguo Li und Yizhou Yao. „Radar-Embedded Communication Waveform Design Based on Parameter Optimization“. Journal of Physics: Conference Series 2404, Nr. 1 (01.12.2022): 012032. http://dx.doi.org/10.1088/1742-6596/2404/1/012032.
Der volle Inhalt der QuelleMetzlaff, Tobias. „Symmetry Adapted Bases for Trigonometric Optimization“. ACM Communications in Computer Algebra 57, Nr. 3 (September 2023): 137–40. http://dx.doi.org/10.1145/3637529.3637535.
Der volle Inhalt der QuelleHu, En-Liang, und Bo Wang. „A new optimization in SDP-based learning“. Neurocomputing 365 (November 2019): 10–20. http://dx.doi.org/10.1016/j.neucom.2019.06.058.
Der volle Inhalt der QuelleHu, Haijiang, Shaojing Song und Fengdeng Zhang. „FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization“. Journal of Electrical and Computer Engineering 2020 (20.02.2020): 1–7. http://dx.doi.org/10.1155/2020/4503706.
Der volle Inhalt der QuelleKANNO, Y., M. OHSAKI und N. KATOH. „SEQUENTIAL SEMIDEFINITE PROGRAMMING FOR OPTIMIZATION OF FRAMED STRUCTURES UNDER MULTIMODAL BUCKLING CONSTRAINTS“. International Journal of Structural Stability and Dynamics 01, Nr. 04 (Dezember 2001): 585–602. http://dx.doi.org/10.1142/s0219455401000305.
Der volle Inhalt der QuelleGil-González, Walter, Alexander Molina-Cabrera, Oscar Danilo Montoya und 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, Nr. 21 (30.10.2020): 7681. http://dx.doi.org/10.3390/app10217681.
Der volle Inhalt der QuelleRen, Fangyu, Huotao Gao, Lijuan Yang und Sang Zhou. „Distributed Multistatic Sky-Wave Over-the-Horizon Radar’s Positioning Algorithm for the Marine Target“. International Journal of Antennas and Propagation 2021 (27.10.2021): 1–7. http://dx.doi.org/10.1155/2021/1028784.
Der volle Inhalt der QuelleNandyala, Raja Thejaswini, und 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, Nr. 4 (01.12.2023): 2022. http://dx.doi.org/10.11591/ijai.v12.i4.pp2022-2032.
Der volle Inhalt der QuelleGuolei, Tang, Zhou Huicheng und Li Ningning. „Reservoir optimization model incorporating inflow forecasts with various lead times as hydrologic state variables“. Journal of Hydroinformatics 12, Nr. 3 (24.11.2009): 292–302. http://dx.doi.org/10.2166/hydro.2009.088.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleKhan, Ejaz. „Techniques itératives pour les systèmes CDMA et algorithmes de détection MIMO“. Paris, ENST, 2003. http://www.theses.fr/2003ENST0020.
Der volle Inhalt der QuelleWe 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.
Der volle Inhalt der QuelleNiu, 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.
Der volle Inhalt der QuelleFraticelli, 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.
Der volle Inhalt der QuellePh. 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.
Der volle Inhalt der QuelleHalalchi, Houssem. „Commande linéaire à paramètres variants des robots manipulateurs flexibles“. Phd thesis, Université de Strasbourg, 2012. http://tel.archives-ouvertes.fr/tel-00762367.
Der volle Inhalt der QuelleMonori, Akos. „Task assignment optimization in SAP Extended WarehouseManagement“. Thesis, Högskolan Dalarna, Datateknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3598.
Der volle Inhalt der QuelleGul, 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.
Der volle Inhalt der QuelleMathews, Steffy Ann. „Optimization of an SDR Based Aerial Base Station“. Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011834/.
Der volle Inhalt der QuelleBücher zum Thema "SDP optimization"
SAP performance optimization guide. 6. Aufl. Bonn: Galileo Press, 2011.
Den vollen Inhalt der Quelle findenSAP performance optimization guide: Analyzing and tuning SAP systems. 7. Aufl. Bonn: Galileo Press, 2013.
Den vollen Inhalt der Quelle findenSAP R/3 performance optimization: The official SAP guide. San Francisco: Sybex, 1999.
Den vollen Inhalt der Quelle findenChristensen, Jesper. SAP BW: Administration and performance optimization. Bonn: Galileo Press, 2014.
Den vollen Inhalt der Quelle findenCorporation, International Business Machines, Hrsg. DB2 optimization techniques for SAP database migration and Unicode conversion. [Poughkeepsie, N.Y.?]: IBM Corporation, International Technical Support Organization, 2009.
Den vollen Inhalt der Quelle findenservice), SpringerLink (Online, Hrsg. Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE. New York, NY: Springer New York, 2013.
Den vollen Inhalt der Quelle findenNeureither, A. SAP System Landscape Optimization. SAP press, 2004.
Den vollen Inhalt der Quelle findenSAP Performance Optimization Guide. SAP Press, 2002.
Den vollen Inhalt der Quelle findenInventory Optimization with SAP. Rheinwerk Publishing Inc., 2009.
Den vollen Inhalt der Quelle findenSAP Performance Optimization Guide. 3. Aufl. SAP Press, 2003.
Den vollen Inhalt der Quelle findenBuchteile zum Thema "SDP optimization"
Luo, Zhi-Quan, Jos F. Sturm und 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.
Der volle Inhalt der QuelleShamsi, Davood, Nicole Taheri, Zhisu Zhu und 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.
Der volle Inhalt der QuelleNavascués, Miguel, Stefano Pironio und 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.
Der volle Inhalt der QuelleSotirov, 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.
Der volle Inhalt der QuelleLemaréchal, Claude, und 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.
Der volle Inhalt der QuelleLasserre, 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.
Der volle Inhalt der QuelleElbassioni, Khaled, und 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.
Der volle Inhalt der QuelleLasserre, 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.
Der volle Inhalt der QuelleKim, Sunyoung, und 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.
Der volle Inhalt der QuelleHsieh, Jun-Ting, Pravesh K. Kothari, Lucas Pesenti und 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.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "SDP optimization"
White, Jules, und 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.
Der volle Inhalt der QuelleSanmugadas, Varakini, und 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.
Der volle Inhalt der QuelleLee, Soomin, und 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.
Der volle Inhalt der QuelleWu, Liangting, und 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.
Der volle Inhalt der QuelleZhang, Qinghong, Gang Chen und 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.
Der volle Inhalt der QuelleKrechetov, Mikhail, Jakub Marecek, Yury Maximov und 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.
Der volle Inhalt der QuelleAlsaleh, Ibrahim, Lingling Fan und 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.
Der volle Inhalt der QuelleTomasin, Stefano, und 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.
Der volle Inhalt der QuelleAllen-Zhu, Zeyuan, Yin Tat Lee und 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.
Der volle Inhalt der QuelleRapoport, Lev, und 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.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "SDP optimization"
Alwan, Iktimal, Dennis D. Spencer und Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, Dezember 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.
Der volle Inhalt der QuelleOblow, E. M. STP: A Stochastic Tunneling Algorithm for Global Optimization. Office of Scientific and Technical Information (OSTI), Mai 1999. http://dx.doi.org/10.2172/814395.
Der volle Inhalt der QuelleOron, Gideon, Raphi Mandelbaum, Carlos E. Enriquez, Robert Armon, Yoseph Manor, L. Gillerman, A. Alum und Charles P. Gerba. Optimization of Secondary Wastewater Reuse to Minimize Environmental Risks. United States Department of Agriculture, Dezember 1999. http://dx.doi.org/10.32747/1999.7573077.bard.
Der volle Inhalt der QuelleKing, Wayne. Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, Mai 2023. http://dx.doi.org/10.4271/epr2023011.
Der volle Inhalt der QuelleKolodziejczyk, Bart. Emergence of Quantum Computing Technologies in Automotive Applications: Opportunities and Future Use Cases. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, April 2024. http://dx.doi.org/10.4271/epr2024008.
Der volle Inhalt der QuelleBleuel, D. L., und R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), Februar 1996. http://dx.doi.org/10.2172/212700.
Der volle Inhalt der QuelleBleuel, B. L., und R. J. Donahue. Optimization of the {sup 7}Li(p,n) proton beam energy for BNCT applications. Office of Scientific and Technical Information (OSTI), Mai 1996. http://dx.doi.org/10.2172/273022.
Der volle Inhalt der QuelleHeinkenschloss, Matthias, Denis Ridzal und Miguel Antonio Aguilo. Numerical study of a matrix-free trust-region SQP method for equality constrained optimization. Office of Scientific and Technical Information (OSTI), Dezember 2011. http://dx.doi.org/10.2172/1038211.
Der volle Inhalt der QuelleKhan, Samir. Towards MRO 4.0: Challenges for Digitalization and Mapping Emerging Technologies. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, April 2023. http://dx.doi.org/10.4271/epr2023007.
Der volle Inhalt der QuelleWeller, Joel I., Ignacy Misztal und Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, März 2015. http://dx.doi.org/10.32747/2015.7594404.bard.
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