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Статті в журналах з теми "Active Set Newton Algorithm"
Liu, Hanger, Yan Li, and Maojun Zhang. "An Active Set Limited Memory BFGS Algorithm for Machine Learning." Symmetry 14, no. 2 (February 14, 2022): 378. http://dx.doi.org/10.3390/sym14020378.
Повний текст джерелаLiang, Xi-ming. "Active set truncated-newton algorithm for simultaneous optimization of distillation column." Journal of Central South University of Technology 12, no. 1 (February 1, 2005): 93–96. http://dx.doi.org/10.1007/s11771-005-0211-x.
Повний текст джерелаSan Juan Sebastián, Pablo, Tuomas Virtanen, Victor M. Garcia-Molla, and Antonio M. Vidal. "Analysis of an efficient parallel implementation of active-set Newton algorithm." Journal of Supercomputing 75, no. 3 (May 19, 2018): 1298–309. http://dx.doi.org/10.1007/s11227-018-2423-5.
Повний текст джерелаVirtanen, Tuomas, Jort Florent Gemmeke, and Bhiksha Raj. "Active-Set Newton Algorithm for Overcomplete Non-Negative Representations of Audio." IEEE Transactions on Audio, Speech, and Language Processing 21, no. 11 (November 2013): 2277–89. http://dx.doi.org/10.1109/tasl.2013.2263144.
Повний текст джерелаSun, Li, Guoping He, Yongli Wang, and Changyin Zhou. "An accurate active set newton algorithm for large scale bound constrained optimization." Applications of Mathematics 56, no. 3 (May 20, 2011): 297–314. http://dx.doi.org/10.1007/s10492-011-0018-z.
Повний текст джерелаEl-Alem, Mahmoud M., Mohammedi R. Abdel-Aziz, and Amr S. El-Bakry. "A projected Hessian Gauss-Newton algorithm for solving systems of nonlinear equations and inequalities." International Journal of Mathematics and Mathematical Sciences 25, no. 6 (2001): 397–409. http://dx.doi.org/10.1155/s0161171201002290.
Повний текст джерелаFacchinei, Francisco, Joaquim Júdice, and João Soares. "An Active Set Newton Algorithm for Large-Scale Nonlinear Programs with Box Constraints." SIAM Journal on Optimization 8, no. 1 (February 1998): 158–86. http://dx.doi.org/10.1137/s1052623493253991.
Повний текст джерелаJodlbauer, Daniel, Ulrich Langer, and Thomas Wick. "Parallel Matrix-Free Higher-Order Finite Element Solvers for Phase-Field Fracture Problems." Mathematical and Computational Applications 25, no. 3 (July 7, 2020): 40. http://dx.doi.org/10.3390/mca25030040.
Повний текст джерелаLai, Shu-Zhen, Hou-Biao Li, and Zu-Tao Zhang. "A Symmetric Rank-One Quasi-Newton Method for Nonnegative Matrix Factorization." ISRN Applied Mathematics 2014 (January 22, 2014): 1–11. http://dx.doi.org/10.1155/2014/846483.
Повний текст джерелаFalocco, S., F. J. Carrera, and J. Larsson. "Automated algorithms to build active galactic nucleus classifiers." Monthly Notices of the Royal Astronomical Society 510, no. 1 (November 27, 2021): 161–76. http://dx.doi.org/10.1093/mnras/stab3435.
Повний текст джерелаДисертації з теми "Active Set Newton Algorithm"
Mishchenko, Kateryna. "Numerical Algorithms for Optimization Problems in Genetical Analysis." Doctoral thesis, Västerås : Scool of education, Culture and Communication, Mälardalen University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-650.
Повний текст джерелаMair, Patrick, Kurt Hornik, and Leeuw Jan de. "Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods." American Statistical Association, 2009. http://epub.wu.ac.at/3993/1/isotone.pdf.
Повний текст джерелаChin, Choong Ming. "A new trust region based SLP filter algorithm which uses EQP active set strategy." Thesis, University of Dundee, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573094.
Повний текст джерелаJacmenovic, Dennis, and dennis_jacman@yahoo com au. "Optimisation of Active Microstrip Patch Antennas." RMIT University. Electrical and Computer Engineering, 2004. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20060307.144507.
Повний текст джерелаJohansson, Sven. "Active Control of Propeller-Induced Noise in Aircraft : Algorithms & Methods." Doctoral thesis, Karlskrona, Ronneby : Blekinge Institute of Technology, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00171.
Повний текст джерелаBuller i vår dagliga miljö kan ha en negativ inverkan på vår hälsa. I många sammanhang, i tex bilar, båtar och flygplan, förekommer lågfrekvent buller. Lågfrekvent buller är oftast inte skadligt för hörseln, men kan vara tröttande och försvåra konversationen mellan personer som vistas i en utsatt miljö. En dämpning av bullernivån medför en förbättrad taluppfattbarhet samt en komfortökning. Att dämpa lågfrekvent buller med traditionella passiva metoder, tex absorbenter och reflektorer, är oftast ineffektivt. Det krävs stora, skrymmande absorbenter för att dämpa denna typ av buller samt tunga skiljeväggar för att förhindra att bullret transmitteras vidare från ett utrymme till ett annat. Metoder som är mera lämpade vid dämpning av lågfrekvent buller är de aktiva. De aktiva metoderna baseras på att en vågrörelse som ligger i motfas med en annan överlagras och de släcker ut varandra. Bullerdämpningen erhålls genom att ett ljudfält genereras som är lika starkt som bullret men i motfas med detta. De aktiva bullerdämpningsmetoderna medför en effektiv dämpning av lågfrekvent buller samtidigt som volymen, tex hos bilkupen eller båt/flygplanskabinen ej påverkas nämnvärt. Dessutom kan fordonets/farkostens vikt reduceras vilket är tacksamt för bränsleförbrukningen. I de flesta tillämpningar varierar bullrets karaktär, dvs styrka och frekvensinnehåll. För att följa dessa variationer krävs ett adaptivt (självinställande) reglersystem som styr genereringen av motljudet. I propellerflygplan är de dominerande frekvenserna i kabinbullret relaterat till propellrarnas varvtal, man känner alltså till frekvenserna som skall dämpas. Man utnyttjar en varvtalssignal för att generera signaler, så kallade referenssignaler, med de frekvenser som skall dämpas. Dessa bearbetas av ett reglersystem som generar signaler till högtalarna som i sin tur generar motljudet. För att ställa in högtalarsignalerna så att en effektiv dämpning erhålls, används mikrofoner utplacerade i kabinen som mäter bullret. För att åstadkomma en effektiv bullerdämpning i ett rum, tex i en flygplanskabin, behövs flera högtalare och mikrofoner, vilket kräver ett avancerat reglersystem. I doktorsavhandlingen ''Active Control of Propeller-Induced Noise in Aircraft'' behandlas olika metoder för att reducera kabinbuller härrörande från propellrarna. Här presenteras olika strukturer på reglersystem samt beräkningsalgoritmer för att ställa in systemet. För stora system där många högtalare och mikrofoner används, samt flera frekvenser skall dämpas, är det viktigt att systemet inte behöver för stor beräkningskapacitet för att generera motljudet. Metoderna som behandlas ger en effektiv dämpning till låg beräkningskostnad. Delar av materialet som presenteras i avhandlingen har ingått i ett EU-projekt med inriktning mot bullerundertryckning i propellerflygplan. I projektet har flera europeiska flygplanstillverkare deltagit. Avhandlingen behandlar även aktiv bullerdämpning i headset, som används av helikopterpiloter. I denna tillämpning har aktiv bullerdämpning används för att öka taluppfattbarheten.
Vie, Jean-Léopold. "Second-order derivatives for shape optimization with a level-set method." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1072/document.
Повний текст джерелаThe main purpose of this thesis is the definition of a shape optimization method which combines second-order differentiationwith the representation of a shape by a level-set function. A second-order method is first designed for simple shape optimization problems : a thickness parametrization and a discrete optimization problem. This work is divided in four parts.The first one is bibliographical and contains different necessary backgrounds for the rest of the work. Chapter 1 presents the classical results for general optimization and notably the quadratic rate of convergence of second-order methods in well-suited cases. Chapter 2 is a review of the different modelings for shape optimization while Chapter 3 details two particular modelings : the thickness parametrization and the geometric modeling. The level-set method is presented in Chapter 4 and Chapter 5 recalls the basics of the finite element method.The second part opens with Chapter 6 and Chapter 7 which detail the calculation of second-order derivatives for the thickness parametrization and the geometric shape modeling. These chapters also focus on the particular structures of the second-order derivative. Then Chapter 8 is concerned with the computation of discrete derivatives for shape optimization. Finally Chapter 9 deals with different methods for approximating a second-order derivative and the definition of a second-order algorithm in a general modeling. It is also the occasion to make a few numerical experiments for the thickness (defined in Chapter 6) and the discrete (defined in Chapter 8) modelings.Then, the third part is devoted to the geometric modeling for shape optimization. It starts with the definition of a new framework for shape differentiation in Chapter 10 and a resulting second-order method. This new framework for shape derivatives deals with normal evolutions of a shape given by an eikonal equation like in the level-set method. Chapter 11 is dedicated to the numerical computation of shape derivatives and Chapter 12 contains different numerical experiments.Finally the last part of this work is about the numerical analysis of shape optimization algorithms based on the level-set method. Chapter 13 is concerned with a complete discretization of a shape optimization algorithm. Chapter 14 then analyses the numerical schemes for the level-set method, and the numerical error they may introduce. Finally Chapter 15 details completely a one-dimensional shape optimization example, with an error analysis on the rates of convergence
Costa, Carlos Ednaldo Ueno. "O Método de Newton e a Função Penalidade Quadrática aplicados ao problema de fluxo de potência ótimo." Universidade de São Paulo, 1998. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-27112017-145520/.
Повний текст джерелаThis work presents an approach on Newton\'s Method associated with the quadratic penalty function and the active set methods in the solution of Optimal Power Flow Problem (OPF). The general formulation of the OPF problem is presented, as will as the technique used in the equation systems resolution. The Lagrangean matrix factorization is carried out by elements instead of structures in blocks. The characteristic of sparsity of the Lagrangean matrix is taken in to account. Numerical results of tests realized in systems of 3, 14, 30 and 118 buses are presented to show the efficiency of the method.
Lewis, Andrew. "Parallel Optimisation Algorithms for Continuous, Non-Linear Numerical solutions." Thesis, Griffith University, 2004. http://hdl.handle.net/10072/367382.
Повний текст джерелаThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Computing and Information Technology
Full Text
Cheng, Jianqiang. "Stochastic Combinatorial Optimization." Thesis, Paris 11, 2013. http://www.theses.fr/2013PA112261.
Повний текст джерелаIn this thesis, we studied three types of stochastic problems: chance constrained problems, distributionally robust problems as well as the simple recourse problems. For the stochastic programming problems, there are two main difficulties. One is that feasible sets of stochastic problems is not convex in general. The other main challenge arises from the need to calculate conditional expectation or probability both of which are involving multi-dimensional integrations. Due to the two major difficulties, for all three studied problems, we solved them with approximation approaches.We first study two types of chance constrained problems: linear program with joint chance constraints problem (LPPC) as well as maximum probability problem (MPP). For both problems, we assume that the random matrix is normally distributed and its vector rows are independent. We first dealt with LPPC which is generally not convex. We approximate it with two second-order cone programming (SOCP) problems. Furthermore under mild conditions, the optimal values of the two SOCP problems are a lower and upper bounds of the original problem respectively. For the second problem, we studied a variant of stochastic resource constrained shortest path problem (called SRCSP for short), which is to maximize probability of resource constraints. To solve the problem, we proposed to use a branch-and-bound framework to come up with the optimal solution. As its corresponding linear relaxation is generally not convex, we give a convex approximation. Finally, numerical tests on the random instances were conducted for both problems. With respect to LPPC, the numerical results showed that the approach we proposed outperforms Bonferroni and Jagannathan approximations. While for the MPP, the numerical results on generated instances substantiated that the convex approximation outperforms the individual approximation method.Then we study a distributionally robust stochastic quadratic knapsack problems, where we only know part of information about the random variables, such as its first and second moments. We proved that the single knapsack problem (SKP) is a semedefinite problem (SDP) after applying the SDP relaxation scheme to the binary constraints. Despite the fact that it is not the case for the multidimensional knapsack problem (MKP), two good approximations of the relaxed version of the problem are provided which obtain upper and lower bounds that appear numerically close to each other for a range of problem instances. Our numerical experiments also indicated that our proposed lower bounding approximation outperforms the approximations that are based on Bonferroni's inequality and the work by Zymler et al.. Besides, an extensive set of experiments were conducted to illustrate how the conservativeness of the robust solutions does pay off in terms of ensuring the chance constraint is satisfied (or nearly satisfied) under a wide range of distribution fluctuations. Moreover, our approach can be applied to a large number of stochastic optimization problems with binary variables.Finally, a stochastic version of the shortest path problem is studied. We proved that in some cases the stochastic shortest path problem can be greatly simplified by reformulating it as the classic shortest path problem, which can be solved in polynomial time. To solve the general problem, we proposed to use a branch-and-bound framework to search the set of feasible paths. Lower bounds are obtained by solving the corresponding linear relaxation which in turn is done using a Stochastic Projected Gradient algorithm involving an active set method. Meanwhile, numerical examples were conducted to illustrate the effectiveness of the obtained algorithm. Concerning the resolution of the continuous relaxation, our Stochastic Projected Gradient algorithm clearly outperforms Matlab optimization toolbox on large graphs
Vijay, Girish Venkata K. "Speech and noise analysis using sparse representation and acoustic-phonetics knowledge." Thesis, 2017. https://etd.iisc.ac.in/handle/2005/4481.
Повний текст джерелаКниги з теми "Active Set Newton Algorithm"
Kaspina, Roza, and Lyubov' Plotnikova. Accounting and taxation of foreign economic activities of organizations. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1018339.
Повний текст джерелаvan der Hulst, Harry. The RcvP Model. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198813576.003.0002.
Повний текст джерелаЧастини книг з теми "Active Set Newton Algorithm"
Kanzow, Christian. "An Active Set-Type Newton Method for Constrained Nonlinear Systems." In Complementarity: Applications, Algorithms and Extensions, 179–200. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3279-5_9.
Повний текст джерелаRousselle, Jean-Jacques, Nicole Vincent, and Nicolas Verbeke. "Genetic Algorithm to Set Active Contour." In Computer Analysis of Images and Patterns, 345–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45179-2_43.
Повний текст джерелаHager, William W. "The LP Dual Active Set Algorithm." In Applied Optimization, 243–54. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4613-3279-4_16.
Повний текст джерелаZhang, Lihui, Siriphong Lawphongpanich, and Yafeng Yin. "An Active-set Algorithm for Discrete Network Design Problems." In Transportation and Traffic Theory 2009: Golden Jubilee, 283–300. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0820-9_14.
Повний текст джерелаDumont, Georges. "The Active Set Algorithm for Solving Frictionless Unilateral Contact Problems." In Contact Mechanics, 263–66. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1983-6_35.
Повний текст джерелаMaška, Martin, Pavel Matula, Ondřej Daněk, and Michal Kozubek. "A Fast Level Set-Like Algorithm for Region-Based Active Contours." In Advances in Visual Computing, 387–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17277-9_40.
Повний текст джерелаShao, Chenggang, Xiaojun Jing, Songlin Sun, and Yueming Lu. "Active RFID-Based Indoor Localization Algorithm Using Virtual Reference through Bivariate Newton Interpolation." In Trustworthy Computing and Services, 186–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35795-4_24.
Повний текст джерелаShujin, Chen, and Zhang Junjun. "Group Control Strategy of Welding Machine Based on Improved Active Set Algorithm." In Lecture Notes in Electrical Engineering, 219–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21762-3_28.
Повний текст джерелаSuzuki, Kenji. "Computerized Segmentation of Organs by Means of Geodesic Active-Contour Level-Set Algorithm." In Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies, 103–28. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-8195-0_4.
Повний текст джерелаZdunek, Rafal. "Regularized Active Set Least Squares Algorithm for Nonnegative Matrix Factorization in Application to Raman Spectra Separation." In Advances in Computational Intelligence, 492–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21498-1_62.
Повний текст джерелаТези доповідей конференцій з теми "Active Set Newton Algorithm"
Virtanen, Tuomas, Bhiksha Raj, Jort F. Gemmeke, and Hugo Van hamme. "Active-set newton algorithm for non-negative sparse coding of audio." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6854169.
Повний текст джерелаSarmiento Vega, Auxiliadora, Ivan Duran Diaz, Irene Fondon, and Sergio Cruces. "Generalization of an Active Set Newton Algorithm with Alpha-Beta divergences for audio separation." In 2021 29th European Signal Processing Conference (EUSIPCO). IEEE, 2021. http://dx.doi.org/10.23919/eusipco54536.2021.9616330.
Повний текст джерелаIto, Kazufumi, and Karl Kunisch. "Nonsmooth Optimization Method for Image Restoration." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0673.
Повний текст джерелаYu, Haodong. "A Smoothing Active-Set Newton Method for Constrained Optimization." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.95.
Повний текст джерелаHeylen, Rob, and Paul Scheunders. "Hyperspectral unmixing using an active set algorithm." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7025139.
Повний текст джерелаShujin Chen, Mingfang Wu, and Zhongmin Lai. "PMSM drive system control based on improved active set algorithm." In 2008 Chinese Control and Decision Conference (CCDC). IEEE, 2008. http://dx.doi.org/10.1109/ccdc.2008.4597912.
Повний текст джерелаTzannetakis, N., and P. Y. Papalambros. "An Active Set Sequential Linearization Algorithm for Nonlinear Design Optimization." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0001.
Повний текст джерелаKlintberg, Emil, Magnus Nilsson, Lars Johannesson Mardh, and Ankit Gupta. "A Primal Active-Set Minimal-Representation Algorithm for Polytopes with Application to Invariant-Set Calculations." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619642.
Повний текст джерелаYou, Chong, Chun-Guang Li, Daniel P. Robinson, and Rene Vidal. "Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering." In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.426.
Повний текст джерелаXiao, Quan, Canhong Wen, and Zirui Yan. "Image denoising via K-SVD with primal-dual active set algorithm." In 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2020. http://dx.doi.org/10.1109/wacv45572.2020.9093569.
Повний текст джерела