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Статті в журналах з теми "Newton algorithms"
Lu, Pei Xin. "Research on BP Neural Network Algorithm Based on Quasi-Newton Method." Applied Mechanics and Materials 686 (October 2014): 388–94. http://dx.doi.org/10.4028/www.scientific.net/amm.686.388.
Повний текст джерелаKISETA, Jacques SABITI, and 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, no. 3 (November 9, 2021): 1–17. http://dx.doi.org/10.47285/isr.v2i3.106.
Повний текст джерелаXu, Xiang-Rong, Won-Jee Chung, Young-Hyu Choi, and Xiang-Feng Ma. "A new dynamic formulation for robot manipulators containing closed kinematic chains." Robotica 17, no. 3 (May 1999): 261–67. http://dx.doi.org/10.1017/s0263574799001320.
Повний текст джерелаDussault, Jean-Pierre. "High-order Newton-penalty algorithms." Journal of Computational and Applied Mathematics 182, no. 1 (October 2005): 117–33. http://dx.doi.org/10.1016/j.cam.2004.11.043.
Повний текст джерелаCai, Xiao-Chuan, and David E. Keyes. "Nonlinearly Preconditioned Inexact Newton Algorithms." SIAM Journal on Scientific Computing 24, no. 1 (January 2002): 183–200. http://dx.doi.org/10.1137/s106482750037620x.
Повний текст джерелаGościniak, Ireneusz, and Krzysztof Gdawiec. "Visual Analysis of Dynamics Behaviour of an Iterative Method Depending on Selected Parameters and Modifications." Entropy 22, no. 7 (July 2, 2020): 734. http://dx.doi.org/10.3390/e22070734.
Повний текст джерелаTaher, Mardeen Sh, and Salah G. Shareef. "A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula." International Journal of Analysis and Applications 21 (April 3, 2023): 31. http://dx.doi.org/10.28924/2291-8639-21-2023-31.
Повний текст джерелаZhang, 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.
Повний текст джерелаBo, Liefeng, Ling Wang, and Licheng Jiao. "Recursive Finite Newton Algorithm for Support Vector Regression in the Primal." Neural Computation 19, no. 4 (April 2007): 1082–96. http://dx.doi.org/10.1162/neco.2007.19.4.1082.
Повний текст джерелаAghamiry, H. S., A. Gholami, and S. Operto. "Full waveform inversion by proximal Newton method using adaptive regularization." Geophysical Journal International 224, no. 1 (September 11, 2020): 169–80. http://dx.doi.org/10.1093/gji/ggaa434.
Повний текст джерелаДисертації з теми "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.
Повний текст джерелаCataloged 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.
Повний текст джерелаKlemes, Marek Carleton University Dissertation Engineering Electronics. "Fast robust Quasi-Newton adaptive algorithms for general array processing." Ottawa, 1996.
Знайти повний текст джерелаGhandhari, 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.
Повний текст джерелаHarrison, Anthony Westbrook. "Algorithms for Computing the Lattice Size." Kent State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1529781033957183.
Повний текст джерелаSassi, Carlos Alberto. "Sobre o desempenho de métodos Quase-Newton e aplicações." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306041.
Повний текст джерелаDissertação (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.
Повний текст джерелаDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
Made available in DSpace on 2018-08-04T05:03:19Z (GMT). No. of bitstreams: 1 Gaujoux_RenaudGilles_M.pdf: 1743739 bytes, checksum: a3548a59bc983f4398cb0136c62c1d6a (MD5) Previous issue date: 2005
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.
Повний текст джерелаZanjácomo, 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.
Повний текст джерелаHüeber, 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.
Повний текст джерелаКниги з теми "Newton algorithms"
Kuan, Chung-Ming. A recurrent Newton algorithm and its convergence properties. Champaign: University of Illinois at Urbana-Champaign, 1993.
Знайти повний текст джерелаDeuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.
Знайти повний текст джерелаD, Gropp W., and 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.
Знайти повний текст джерела1962-, Cai Xiao-Chuan, Institute for Computer Applications in Science and Engineering., and 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.
Знайти повний текст джерелаD, Gropp W., and 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.
Знайти повний текст джерела1962-, Cai Xiao-Chuan, and 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.
Знайти повний текст джерела1962-, Cai Xiao-Chuan, and 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.
Знайти повний текст джерела1962-, Cai Xiao-Chuan, and 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.
Знайти повний текст джерелаPaul, Casasent David, Hall Ernest L, and 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.
Знайти повний текст джерелаKostyukov, Viktor. Molecular mechanics of biopolymers. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1010677.
Повний текст джерелаЧастини книг з теми "Newton algorithms"
Sima, Vasile. "Newton Algorithms." In Algorithms for Linear-Quadratic Optimization, 97–196. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003067450-2.
Повний текст джерелаBhatnagar, S., H. Prasad, and L. Prashanth. "Newton-Based Smoothed Functional Algorithms." In Stochastic Recursive Algorithms for Optimization, 133–48. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4285-0_8.
Повний текст джерелаBhatnagar, S., H. Prasad, and L. Prashanth. "Newton-Based Simultaneous Perturbation Stochastic Approximation." In Stochastic Recursive Algorithms for Optimization, 105–31. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4285-0_7.
Повний текст джерелаSchröter, M., and O. Sauer. "Quasi-Newton Algorithms for Medical Image Registration." In IFMBE Proceedings, 433–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03882-2_115.
Повний текст джерелаPedersen, C., and P. Thoft-Christensen. "Interactive Structural Optimization with Quasi-Newton Algorithms." In 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.
Повний текст джерелаSommars, Jeff, and Jan Verschelde. "Pruning Algorithms for Pretropisms of Newton Polytopes." In Computer Algebra in Scientific Computing, 489–503. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45641-6_31.
Повний текст джерелаKanzow, 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 джерелаEvtushenko, Yu G., and V. G. Zhadan. "Stable Barrier-Projection and Barrier-Newton Methods for Linear and Nonlinear Programming." In Algorithms for Continuous Optimization, 255–85. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-009-0369-2_9.
Повний текст джерелаPoloni, Federico. "Newton method for rank-structured algebraic Riccati equations." In 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.
Повний текст джерелаChristensen, Peter W., and Jong-Shi Pang. "Frictional Contact Algorithms Based on Semismooth Newton Methods." In 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.
Повний текст джерелаТези доповідей конференцій з теми "Newton algorithms"
Tsinos, Christos G., and Paulo S. R. Diniz. "Data-selective LMS-Newton and LMS-Quasi-Newton Algorithms." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683076.
Повний текст джерелаPillutla, Krishna, Vincent Roulet, Sham M. Kakade, and Zaid Harchaoui. "Modified Gauss-Newton Algorithms under Noise." In 2023 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2023. http://dx.doi.org/10.1109/ssp53291.2023.10207977.
Повний текст джерелаKoshevoy, Gleb, and Denis Mironov. "F-polynomials & Newton polytopes." In 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2022. http://dx.doi.org/10.1109/synasc57785.2022.00017.
Повний текст джерелаBhotto, Md Zulfiquar Ali, and Andreas Antoniou. "Improved data-selective LMS-Newton adaptation algorithms." In 2009 16th International Conference on Digital Signal Processing (DSP). IEEE, 2009. http://dx.doi.org/10.1109/icdsp.2009.5201148.
Повний текст джерелаSingh, V. K., and K. C. Gupta. "A Manipulator Jacobian Based Modified Newton-Raphson Algorithm (JMNR) for Robot Inverse Kinematics." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0142.
Повний текст джерелаMasetti, Giulio, Silvano Chiaradonna, and Felicita di Giandomenico. "Exploring equations ordering influence on variants of the Newton-Raphson method." In 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.
Повний текст джерелаFoltyn, Ladislav, and Oldřich Vlach. "Implementation of full linearization in semismooth Newton method for 2D contact problem." In Programs and Algorithms of Numerical Mathematics 18. Institute of Mathematics, Czech Academy of Sciences, 2017. http://dx.doi.org/10.21136/panm.2016.04.
Повний текст джерелаNikpour, M., J. H. Manton, and R. Mahony. "Novel Newton algorithms for the Hermitian eigenvalue problem." In Information, Decision and Control. IEEE, 2002. http://dx.doi.org/10.1109/idc.2002.995439.
Повний текст джерелаWills, Adrian G., and Thomas B. Schon. "On the construction of probabilistic Newton-type algorithms." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8264638.
Повний текст джерелаTiexiang Li, Eric King-wah Chu, and Xuan Zhao. "Robust pole assignment via the Schur-Newton algorithms." In 2011 International Conference on Multimedia Technology (ICMT). IEEE, 2011. http://dx.doi.org/10.1109/icmt.2011.6002622.
Повний текст джерелаЗвіти організацій з теми "Newton algorithms"
Saleh, R. A., J. K. White, A. R. Newton, and A. L. Sangiovanni-Vincentelli. Accelerating Relaxation Algorithms for Circuit Simulation Using Waveform-Newton and Step-Size Refinement. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada200774.
Повний текст джерелаJoseph, 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), May 2014. http://dx.doi.org/10.2172/1249135.
Повний текст джерелаMcHugh, 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), October 1995. http://dx.doi.org/10.2172/130602.
Повний текст джерелаArhin, Stephen, Babin Manandhar, Hamdiat Baba Adam, and Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, April 2021. http://dx.doi.org/10.31979/mti.2021.1943.
Повний текст джерелаCanonico, Rosangela, and Luca Parisi. The Newman Janis Algorithm: A Review of Some Results. GIQ, 2012. http://dx.doi.org/10.7546/giq-12-2011-159-169.
Повний текст джерелаCanonico, Rosangela, and 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.
Повний текст джерелаAllen, Luke, Joon Lim, Robert Haehnel, and Ian Detwiller. Rotor blade design framework for airfoil shape optimization with performance considerations. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41037.
Повний текст джерела