Literatura académica sobre el tema "Newton algorithms"
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Artículos de revistas sobre el tema "Newton algorithms"
Lu, Pei Xin. "Research on BP Neural Network Algorithm Based on Quasi-Newton Method". Applied Mechanics and Materials 686 (octubre de 2014): 388–94. http://dx.doi.org/10.4028/www.scientific.net/amm.686.388.
Texto completoKISETA, Jacques SABITI y Roger LIENDI AKUMOSO. "A Review of Well-Known Robust Line Search and Trust Region Numerical Optimization Algorithms for Solving Nonlinear Least-Squares Problems". International Science Review 2, n.º 3 (9 de noviembre de 2021): 1–17. http://dx.doi.org/10.47285/isr.v2i3.106.
Texto completoXu, Xiang-Rong, Won-Jee Chung, Young-Hyu Choi y Xiang-Feng Ma. "A new dynamic formulation for robot manipulators containing closed kinematic chains". Robotica 17, n.º 3 (mayo de 1999): 261–67. http://dx.doi.org/10.1017/s0263574799001320.
Texto completoDussault, Jean-Pierre. "High-order Newton-penalty algorithms". Journal of Computational and Applied Mathematics 182, n.º 1 (octubre de 2005): 117–33. http://dx.doi.org/10.1016/j.cam.2004.11.043.
Texto completoCai, Xiao-Chuan y David E. Keyes. "Nonlinearly Preconditioned Inexact Newton Algorithms". SIAM Journal on Scientific Computing 24, n.º 1 (enero de 2002): 183–200. http://dx.doi.org/10.1137/s106482750037620x.
Texto completoGościniak, Ireneusz y Krzysztof Gdawiec. "Visual Analysis of Dynamics Behaviour of an Iterative Method Depending on Selected Parameters and Modifications". Entropy 22, n.º 7 (2 de julio de 2020): 734. http://dx.doi.org/10.3390/e22070734.
Texto completoTaher, Mardeen Sh y Salah G. Shareef. "A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula". International Journal of Analysis and Applications 21 (3 de abril de 2023): 31. http://dx.doi.org/10.28924/2291-8639-21-2023-31.
Texto completoZhang, Liping. "A Newton-Type Algorithm for Solving Problems of Search Theory". Advances in Operations Research 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/513918.
Texto completoBo, Liefeng, Ling Wang y Licheng Jiao. "Recursive Finite Newton Algorithm for Support Vector Regression in the Primal". Neural Computation 19, n.º 4 (abril de 2007): 1082–96. http://dx.doi.org/10.1162/neco.2007.19.4.1082.
Texto completoAghamiry, H. S., A. Gholami y S. Operto. "Full waveform inversion by proximal Newton method using adaptive regularization". Geophysical Journal International 224, n.º 1 (11 de septiembre de 2020): 169–80. http://dx.doi.org/10.1093/gji/ggaa434.
Texto completoTesis sobre el tema "Newton algorithms"
Wei, Ermin. "Distributed Newton-type algorithms for network resource allocation". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/60822.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (p. 99-101).
Most of today's communication networks are large-scale and comprise of agents with local information and heterogeneous preferences, making centralized control and coordination impractical. This motivated much interest in developing and studying distributed algorithms for network resource allocation problems, such as Internet routing, data collection and processing in sensor networks, and cross-layer communication network design. Existing works on network resource allocation problems rely on using dual decomposition and first-order (gradient or subgradient) methods, which involve simple computations and can be implemented in a distributed manner, yet suffer from slow rate of convergence. Second-order methods are faster, but their direct implementation requires computation intensive matrix inversion operations, which couple information across the network, hence cannot be implemented in a decentralized way. This thesis develops and analyzes Newton-type (second-order) distributed methods for network resource allocation problems. In particular, we focus on two general formulations: Network Utility Maximization (NUM), and network flow cost minimization problems. For NUM problems, we develop a distributed Newton-type fast converging algorithm using the properties of self-concordant utility functions. Our algorithm utilizes novel matrix splitting techniques, which enable both primal and dual Newton steps to be computed using iterative schemes in a decentralized manner with limited information exchange. Moreover, the step-size used in our method can be obtained via an iterative consensus-based averaging scheme. We show that even when the Newton direction and the step-size in our method are computed within some error (due to finite truncation of the iterative schemes), the resulting objective function value still converges superlinearly to an explicitly characterized error neighborhood. Simulation results demonstrate significant convergence rate improvement of our algorithm relative to the existing subgradient methods based on dual decomposition. The second part of the thesis presents a distributed approach based on a Newtontype method for solving network flow cost minimization problems. The key component of our method is to represent the dual Newton direction as the limit of an iterative procedure involving the graph Laplacian, which can be implemented based only on local information. Using standard Lipschitz conditions, we provide analysis for the convergence properties of our algorithm and show that the method converges superlinearly to an explicitly characterized error neighborhood, even when the iterative schemes used for computing the Newton direction and the stepsize are truncated. We also present some simulation results to illustrate the significant performance gains of this method over the subgradient methods currently used.
by Ermin Wei.
S.M.
Saadallah, A. F. "A new approach to quasi-Newton methods for minimization". Thesis, University of Essex, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380374.
Texto completoKlemes, Marek Carleton University Dissertation Engineering Electronics. "Fast robust Quasi-Newton adaptive algorithms for general array processing". Ottawa, 1996.
Buscar texto completoGhandhari, R. A. "On the use of function values to improve quasi-Newton methods". Thesis, University of Essex, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328658.
Texto completoHarrison, Anthony Westbrook. "Algorithms for Computing the Lattice Size". Kent State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1529781033957183.
Texto completoSassi, Carlos Alberto. "Sobre o desempenho de métodos Quase-Newton e aplicações". [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306041.
Texto completoDissertação (mestrado profissional) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
Made available in DSpace on 2018-08-16T22:41:08Z (GMT). No. of bitstreams: 1 Sassi_Carlos_M.pdf: 2431422 bytes, checksum: 7e2d7456777a9a43cc62a5524d3fca93 (MD5) Previous issue date: 2010
Resumo: Iniciamos este trabalho com o estudo de equações não lineares, transcendentais de uma única variável, com o objetivo principal de abordar sistemas de equações não lineares, analisar os métodos, algoritmos e realizar testes computacionais, embasados na plataforma MatLab "The Language of Technical computer - R2008a - version 7.6.0.324_. Os algoritmos tratados se referem ao método de Newton, métodos Quase-Newton, método Secante e aplicações, com enfoque na H-equação de Chandrasekhar. Estudamos aspectos de convergência de cada um destes métodos que puderam ser analisados na prática, a partir dos experimentos numéricos realizados
Abstract: This work begins with the study of nonlinear and transcendental equations, with only one variable, which has the main purpose to study systems of nonlinear equations, methods and algoritms, in order to accomplish computational tests using MatLab Codes "The Language of Technical computer - R2008a - version 7.6.0.324". These algoritms were concerned to Newton's method, Quasi-Newton method, Secant method, and the main application was the Chandrasekhar H-Equation. Convergence studies for these methods were analysed with the applied numerical methods
Mestrado
Matematica
Mestre em Matemática
Gaujoux, Renaud Gilles. "Resolução de sistema KKT por metodo de tipo Newton não diferenciavel". [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306442.
Texto completoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Esta dissertação trata da aplicação de um método de tipo Newton generalizado aos sistemas KKT. Graças às funções chamadas de NCP, o sistema KKT pode ser reformulado como uma equação do tipo H(z) = O, onde H é uma função semi-suave. Nos preliminares teóricos apresentamos os conceitos importantes para a análise desse tipo de sistema quando a função involvida não é diferenciável. Trata-se de subdiferencial, semi-suavidade, semi-derivada. Então, usando um ponto de vista global, descrevemos de uma vez só as diferentes generalizações do método de Newton, apresentando as condições suficientes de convergência local. Uma versão globalizada do método é também detalhada. Com o fim de aplicar o algoritmo à reformulação semi-suave do sistema KKT, estudamos as propriedades da função H, primeiro independentemente da função NCP usada. Então analisamos o caso de três funções NCP particulares: a função do Mínimo, a função de Fischer-Burmeister, a função de Fischer-Burmeister Penalizada. Apresentamos os resultados de testes numéricos que comparam o desempenho do algoritmo quando usa as diferentes funções NCP acima
Abstract: This work deals with the use of generalized Newton type method to solve KKT systems. By the mean of so called NCP functions, any KKT system can be writen as an equation of type H(z) = O, where H is a semismooth function. In a teorical preliminaries part, we present some key notions for the analysis of such a type of system, whose the involved function is not differentiable. It deals with subdifferential, semismoothness, semiderivative. Then, tackling the problem with a very general point of view, we make a unified description of different generalizations of N ewton method, giving sufficient local convergence conditions. More over, we detail a possible globalization of such methods. In order to use this global algorithm to solve semismooth form of KKT systems, we study some of the H function's properties, first without specifying any underlying NCP function, and then in the case of three known NCP functions: the minimum function, the Fischer-Burmeister function and the penalized Fischer-Burmeister function. Finally, we give the results of numerical tests, which compare the algorithm's performance for each of these three NCP functions
Mestrado
Matematica Aplicada
Mestre em Matemática Aplicada
Woodgate, K. G. "Optimization over positive semi-definite symmetric matrices with application to Quasi-Newton algorithms". Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/46914.
Texto completoZanjácomo, Paulo Régis. "On weighted paths for nonlinear semidefinite complementarity problems and newton methods for semidefinite programming". Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/21680.
Texto completoHüeber, Stefan. "Discretization techniques and efficient algorithms for contact problems". [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-36087.
Texto completoLibros sobre el tema "Newton algorithms"
Kuan, Chung-Ming. A recurrent Newton algorithm and its convergence properties. Champaign: University of Illinois at Urbana-Champaign, 1993.
Buscar texto completoDeuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.
Buscar texto completoD, Gropp W. y Langley Research Center, eds. Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Buscar texto completo1962-, Cai Xiao-Chuan, Institute for Computer Applications in Science and Engineering. y Langley Research Center, eds. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.
Buscar texto completoD, Gropp W. y Langley Research Center, eds. Globalized Newton-Krylov-Schwarz algorithms and software for parallel implicit CFD. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Buscar texto completo1962-, Cai Xiao-Chuan y Langley Research Center, eds. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.
Buscar texto completo1962-, Cai Xiao-Chuan y Langley Research Center, eds. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.
Buscar texto completo1962-, Cai Xiao-Chuan y Langley Research Center, eds. Parallel Newton-Krylov-Schwarz algorithms for the transonic full potential equation: NASA contract no. NAS1-19480. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.
Buscar texto completoPaul, Casasent David, Hall Ernest L y Society of Photo-optical Instrumentation Engineers., eds. Intelligent robots and computer vision XX: Algorithms, techniques, and active vision : 29-31 October, 2001, Newton [Massachusetts] USA. Bellingham, Wash., USA: SPIE, 2001.
Buscar texto completoKostyukov, Viktor. Molecular mechanics of biopolymers. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1010677.
Texto completoCapítulos de libros sobre el tema "Newton algorithms"
Sima, Vasile. "Newton Algorithms". En Algorithms for Linear-Quadratic Optimization, 97–196. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003067450-2.
Texto completoBhatnagar, S., H. Prasad y L. Prashanth. "Newton-Based Smoothed Functional Algorithms". En Stochastic Recursive Algorithms for Optimization, 133–48. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4285-0_8.
Texto completoBhatnagar, S., H. Prasad y L. Prashanth. "Newton-Based Simultaneous Perturbation Stochastic Approximation". En Stochastic Recursive Algorithms for Optimization, 105–31. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4285-0_7.
Texto completoSchröter, M. y O. Sauer. "Quasi-Newton Algorithms for Medical Image Registration". En IFMBE Proceedings, 433–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03882-2_115.
Texto completoPedersen, C. y P. Thoft-Christensen. "Interactive Structural Optimization with Quasi-Newton Algorithms". En Reliability and Optimization of Structural Systems, 225–32. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34866-7_23.
Texto completoSommars, Jeff y Jan Verschelde. "Pruning Algorithms for Pretropisms of Newton Polytopes". En Computer Algebra in Scientific Computing, 489–503. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45641-6_31.
Texto completoKanzow, Christian. "An Active Set-Type Newton Method for Constrained Nonlinear Systems". En Complementarity: Applications, Algorithms and Extensions, 179–200. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3279-5_9.
Texto completoEvtushenko, Yu G. y V. G. Zhadan. "Stable Barrier-Projection and Barrier-Newton Methods for Linear and Nonlinear Programming". En Algorithms for Continuous Optimization, 255–85. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-009-0369-2_9.
Texto completoPoloni, Federico. "Newton method for rank-structured algebraic Riccati equations". En Algorithms for Quadratic Matrix and Vector Equations, 131–43. Pisa: Scuola Normale Superiore, 2011. http://dx.doi.org/10.1007/978-88-7642-384-0_8.
Texto completoChristensen, Peter W. y Jong-Shi Pang. "Frictional Contact Algorithms Based on Semismooth Newton Methods". En Reformulation: Nonsmooth, Piecewise Smooth, Semismooth and Smoothing Methods, 81–116. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6388-1_5.
Texto completoActas de conferencias sobre el tema "Newton algorithms"
Tsinos, Christos G. y Paulo S. R. Diniz. "Data-selective LMS-Newton and LMS-Quasi-Newton Algorithms". En ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683076.
Texto completoPillutla, Krishna, Vincent Roulet, Sham M. Kakade y Zaid Harchaoui. "Modified Gauss-Newton Algorithms under Noise". En 2023 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2023. http://dx.doi.org/10.1109/ssp53291.2023.10207977.
Texto completoKoshevoy, Gleb y Denis Mironov. "F-polynomials & Newton polytopes". En 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2022. http://dx.doi.org/10.1109/synasc57785.2022.00017.
Texto completoBhotto, Md Zulfiquar Ali y Andreas Antoniou. "Improved data-selective LMS-Newton adaptation algorithms". En 2009 16th International Conference on Digital Signal Processing (DSP). IEEE, 2009. http://dx.doi.org/10.1109/icdsp.2009.5201148.
Texto completoSingh, V. K. y K. C. Gupta. "A Manipulator Jacobian Based Modified Newton-Raphson Algorithm (JMNR) for Robot Inverse Kinematics". En ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0142.
Texto completoMasetti, Giulio, Silvano Chiaradonna y Felicita di Giandomenico. "Exploring equations ordering influence on variants of the Newton-Raphson method". En NUMERICAL COMPUTATIONS: THEORY AND ALGORITHMS (NUMTA–2016): Proceedings of the 2nd International Conference “Numerical Computations: Theory and Algorithms”. Author(s), 2016. http://dx.doi.org/10.1063/1.4965417.
Texto completoFoltyn, Ladislav y Oldřich Vlach. "Implementation of full linearization in semismooth Newton method for 2D contact problem". En Programs and Algorithms of Numerical Mathematics 18. Institute of Mathematics, Czech Academy of Sciences, 2017. http://dx.doi.org/10.21136/panm.2016.04.
Texto completoNikpour, M., J. H. Manton y R. Mahony. "Novel Newton algorithms for the Hermitian eigenvalue problem". En Information, Decision and Control. IEEE, 2002. http://dx.doi.org/10.1109/idc.2002.995439.
Texto completoWills, Adrian G. y Thomas B. Schon. "On the construction of probabilistic Newton-type algorithms". En 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8264638.
Texto completoTiexiang Li, Eric King-wah Chu y Xuan Zhao. "Robust pole assignment via the Schur-Newton algorithms". En 2011 International Conference on Multimedia Technology (ICMT). IEEE, 2011. http://dx.doi.org/10.1109/icmt.2011.6002622.
Texto completoInformes sobre el tema "Newton algorithms"
Saleh, R. A., J. K. White, A. R. Newton y A. L. Sangiovanni-Vincentelli. Accelerating Relaxation Algorithms for Circuit Simulation Using Waveform-Newton and Step-Size Refinement. Fort Belvoir, VA: Defense Technical Information Center, octubre de 1988. http://dx.doi.org/10.21236/ada200774.
Texto completoJoseph, Ilon. Code Coupling via Jacobian-Free Newton-Krylov Algorithms with Application to Magnetized Fluid Plasma and Kinetic Neutral Models. Office of Scientific and Technical Information (OSTI), mayo de 2014. http://dx.doi.org/10.2172/1249135.
Texto completoMcHugh, P. R. An investigation of Newton-Krylov algorithms for solving incompressible and low Mach number compressible fluid flow and heat transfer problems using finite volume discretization. Office of Scientific and Technical Information (OSTI), octubre de 1995. http://dx.doi.org/10.2172/130602.
Texto completoArhin, Stephen, Babin Manandhar, Hamdiat Baba Adam y Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, abril de 2021. http://dx.doi.org/10.31979/mti.2021.1943.
Texto completoCanonico, Rosangela y Luca Parisi. The Newman Janis Algorithm: A Review of Some Results. GIQ, 2012. http://dx.doi.org/10.7546/giq-12-2011-159-169.
Texto completoCanonico, Rosangela y Luca Parisi. Theoretical Models For Astrophysical Objects and the Newman-Janis Algorithm. GIQ, 2012. http://dx.doi.org/10.7546/giq-11-2010-85-96.
Texto completoAllen, Luke, Joon Lim, Robert Haehnel y Ian Detwiller. Rotor blade design framework for airfoil shape optimization with performance considerations. Engineer Research and Development Center (U.S.), junio de 2021. http://dx.doi.org/10.21079/11681/41037.
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