Academic literature on the topic 'Approximation of convex function'
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Journal articles on the topic "Approximation of convex function"
Petrova, T. "One counterexample for convex approximation of function with fractional derivatives, r>4." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 3 (2018): 53–56. http://dx.doi.org/10.17721/1812-5409.2018/3.7.
Full textZala, Vidhi, Mike Kirby, and Akil Narayan. "Structure-Preserving Function Approximation via Convex Optimization." SIAM Journal on Scientific Computing 42, no. 5 (January 2020): A3006—A3029. http://dx.doi.org/10.1137/19m130128x.
Full textJ. J. Koliha. "Approximation of Convex Functions." Real Analysis Exchange 29, no. 1 (2004): 465. http://dx.doi.org/10.14321/realanalexch.29.1.0465.
Full textTang, Wee-Kee. "Sets of differentials and smoothness of convex functions." Bulletin of the Australian Mathematical Society 52, no. 1 (August 1995): 91–96. http://dx.doi.org/10.1017/s0004972700014477.
Full textBosch, Paul. "A Numerical Method for Two-Stage Stochastic Programs under Uncertainty." Mathematical Problems in Engineering 2011 (2011): 1–13. http://dx.doi.org/10.1155/2011/840137.
Full textChen, Xin, Houduo Qi, Liqun Qi, and Kok-Lay Teo. "Smooth Convex Approximation to the Maximum Eigenvalue Function." Journal of Global Optimization 30, no. 2-3 (November 2004): 253–70. http://dx.doi.org/10.1007/s10898-004-8271-2.
Full textUbhaya, Vasant A. "Uniform approximation by quasi-convex and convex functions." Journal of Approximation Theory 55, no. 3 (December 1988): 326–36. http://dx.doi.org/10.1016/0021-9045(88)90099-8.
Full textUbhaya, Vasant A. "Lp approximation by quasi-convex and convex functions." Journal of Mathematical Analysis and Applications 139, no. 2 (May 1989): 574–85. http://dx.doi.org/10.1016/0022-247x(89)90130-3.
Full textZwick, D. "Best Approximation by Convex Functions." American Mathematical Monthly 94, no. 6 (June 1987): 528. http://dx.doi.org/10.2307/2322845.
Full textZwick, D. "Best Approximation by Convex Functions." American Mathematical Monthly 94, no. 6 (June 1987): 528–34. http://dx.doi.org/10.1080/00029890.1987.12000679.
Full textDissertations / Theses on the topic "Approximation of convex function"
Azimi, Roushan Tahere. "Inequalities related to norm and numerical radius of operators." Thesis, Pau, 2020. http://www.theses.fr/2020PAUU3002.
Full textIn this thesis, after expressing concepts and necessary preconditions, we investigate Hermite-Hadamard inequality for geometrically convex functions. Then, by introducing operator geometricallyconvex functions, we extend the results and prove Hermite-Hadamard type inequalityfor these kind of functions. In the following, by proving the log-convexity of somefunctions which are based on the unitarily invariant norm and considering the relation betweengeometrically convex functions and log-convex functions, we present several refinementsfor some well-known operator norm inequalities. Also, we prove operator version ofsome numerical results, which were obtained for approximating a class of convex functions,as an application,we refine Hermite-Hadamard inequality for a class of operator convex functions.Finally, we discuss about the numerical radius of an operator which is equivalent withthe operator norm and we state some related results, and by obtaining some upper boundsfor the Berezin number of an operator which is contained in the numerical range of that operator, we finish the thesis
در این رساله، پس از بیان مفاهیم و مقدمات لازم به بررسی نامساوی هرمیت-هادامار برای توابع محدب هندسی پرداخته سپس با معرفی تابع محدب هندسی عملگری، نتایج را توسیع داده و نامساوی هرمیت-هادامار گونه را برای این دست توابع اثبات می کنیم. در ادامه با نشان دادن محدب لگاریتمی بودن چند تابع که براساس نرم پایای یکانی تعریف شده اند، و با در نظر گرفتن ارتباط بین توابع محدب هندسی و توابع محدب لگاریتمی بهبودهایی از حالت نرمی چند نامساوی عملگری معروف ارائه می دهیم. هم چنین نتایج عددی بدست آمده جهت تقریب رده ای از توابع محدب را برای نسخه عملگری آن ها اثبات نموده و به عنوان کاربردی از نتایج حاصل، نامساوی هرمیت-هادامار را برای برخی توابع محدب عملگری بهبود می بخشیم. در نهایت، در مورد شعاع عددی یک عملگر، که معادل با نرم عملگری آن می باشد بحث نموده و به بیان برخی از نتایج مرتبط پرداخته، و با بدست آوردن کران های بالایی از عدد برزین یک عملگر که زیر مجموعه ای از برد عددی آن عملگر می باشد، رساله را به پایان می بریم
Висоцька, Марія Андріївна. "Модель оптимального податку." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2021. https://ela.kpi.ua/handle/123456789/45204.
Full textThe diploma thesis contains 95 p., 16 fig., 8 tabl, 2 appendices, 11 sources. Theme: optimal tax model. The purpose: to analyze the existing model of the optimal tax, to propose an alternative model and to make a study based on some demonstration data. Objective: analyze the existing model of the optimal tax, propose an alternative model and do research based on some demonstration data. The result of this work is a software product with a user interface that helps to find the optimal tax model for some data and checks it for correctness. At the entrance we receive data on the amount of tax, tax rate and their schedules.
Bose, Gibin. "Approximation H infini, interpolation analytique et optimisation convexe : application à l’adaptation d’impédance large bande." Thesis, Université Côte d'Azur, 2021. http://www.theses.fr/2021COAZ4007.
Full textThe thesis makes an in-depth study of one of the classical problems in RF circuit design,the problem of impedance matching. Matching problem addresses the issue of transmitting the maximum available power from a source to a load within a frequency band. Antennas are one of the classical devices in which impedance matching plays an important role. The design of a matching circuit for a given load primarily amounts to find a lossless scattering matrix which when chained to the load minimize the reflection of power in the total system.In this work, both the theoretical aspects of the broadband matching problem and thepractical applicability of the developed approaches are given due importance. Part I of the thesis covers two different yet closely related approaches to the matching problem. These are based on the classical approaches developed by Helton and Fano-Youla to study the broadband matching problems. The framework established in the first approach entails in finding the best H infinity approximation to an L infinity function, Փ via Nehari's theory. This amounts to reduce the problem to a generalized eigen value problem based on an operator defined on H2, the Hankel operator, HՓ. The realizability of a given gain is provided by the constraint, operator norm of HՓ less than or equal to one. The second approach formulates the matching problem as a convex optimisation problem where in further flexibility is provided to the gain profiles compared to the previous approach. It is based on two rich theories, namely Fano-Youla matching theory and analytic interpolation. The realizabilty of a given gain is based on the Fano-Youla de-embedding conditions which reduces to the positivity of a classical matrix in analytic interpolation theory, the Pick matrix. The concavity of the concerned Pick matrix allows finding the solution to the problem by means of implementing a non-linear semi-definite programming problem. Most importantly, we estimate sharp lower bounds to the matching criterion for finite degree matching circuits and furnish circuits attaining those bounds.Part II of the thesis aims at realizing the matching circuits as ladder networks consisting of inductors and capacitors and discusses some important realizability constraints as well. Matching circuits are designed for several mismatched antennas, testing the robustness of the developed approach. The theory developed in the first part of the thesis provides an efficient way of comparing the matching criterion obtained to the theoretical limits
Lopez, Mario A., Shlomo Reisner, and reisner@math haifa ac il. "Linear Time Approximation of 3D Convex Polytopes." ESI preprints, 2001. ftp://ftp.esi.ac.at/pub/Preprints/esi1005.ps.
Full textFung, Ping-yuen, and 馮秉遠. "Approximation for minimum triangulations of convex polyhedra." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B29809964.
Full textFung, Ping-yuen. "Approximation for minimum triangulations of convex polyhedra." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23273197.
Full textVerschueren, Robin [Verfasser], and Moritz [Akademischer Betreuer] Diehl. "Convex approximation methods for nonlinear model predictive control." Freiburg : Universität, 2018. http://d-nb.info/1192660641/34.
Full textBoiger, Wolfgang Josef. "Stabilised finite element approximation for degenerate convex minimisation problems." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2013. http://dx.doi.org/10.18452/16790.
Full textInfimising sequences of nonconvex variational problems often do not converge strongly in Sobolev spaces due to fine oscillations. These oscillations are physically meaningful; finite element approximations, however, fail to resolve them in general. Relaxation methods replace the nonconvex energy with its (semi)convex hull. This leads to a macroscopic model which is degenerate in the sense that it is not strictly convex and possibly admits multiple minimisers. The lack of control on the primal variable leads to difficulties in the a priori and a posteriori finite element error analysis, such as the reliability-efficiency gap and no strong convergence. To overcome these difficulties, stabilisation techniques add a discrete positive definite term to the relaxed energy. Bartels et al. (IFB, 2004) apply stabilisation to two-dimensional problems and thereby prove strong convergence of gradients. This result is restricted to smooth solutions and quasi-uniform meshes, which prohibit adaptive mesh refinements. This thesis concerns a modified stabilisation term and proves convergence of the stress and, for smooth solutions, strong convergence of gradients, even on unstructured meshes. Furthermore, the thesis derives the so-called flux error estimator and proves its reliability and efficiency. For interface problems with piecewise smooth solutions, a refined version of this error estimator is developed, which provides control of the error of the primal variable and its gradient and thus yields strong convergence of gradients. The refined error estimator converges faster than the flux error estimator and therefore narrows the reliability-efficiency gap. Numerical experiments with five benchmark examples from computational microstructure and topology optimisation complement and confirm the theoretical results.
Schulz, Henrik. "Polyhedral Surface Approximation of Non-Convex Voxel Sets and Improvements to the Convex Hull Computing Method." Forschungszentrum Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:d120-qucosa-27865.
Full textSchulz, Henrik. "Polyhedral Surface Approximation of Non-Convex Voxel Sets and Improvements to the Convex Hull Computing Method." Forschungszentrum Dresden-Rossendorf, 2009. https://hzdr.qucosa.de/id/qucosa%3A21613.
Full textBooks on the topic "Approximation of convex function"
Duality in nonconvex approximation and optimization. New York: Springer, 2005.
Find full textL, Combettes Patrick, and SpringerLink (Online service), eds. Convex Analysis and Monotone Operator Theory in Hilbert Spaces. New York, NY: Springer Science+Business Media, LLC, 2011.
Find full textVasile, Postolică, ed. The best approximation and optimization in locally convex spaces. Frankfurt am Main: P. Lang, 1993.
Find full textKuhn, Daniel. Generalized bounds for convex multistage stochastic programs. Berlin: Springer, 2005.
Find full textGeometric approximation algorithms. Providence, R.I: American Mathematical Society, 2011.
Find full textNikolʹskiĭ, S. M. Izbrannye trudy: V trekh tomakh. Moskva: Nauka, 2006.
Find full textDomich, P. D. A near-optimal starting solution for polynomial approximation of a continuous function in the L. [Washington, D.C.]: U.S. Dept. of Commerce, National Bureau of Standards, 1986.
Find full textDomich, P. D. A near-optimal starting solution for polynomial approximation of a continuous function in the L. [Washington, D.C.]: U.S. Dept. of Commerce, National Bureau of Standards, 1986.
Find full textHedberg, Lars Inge. An axiomatic approach to function spaces, spectral synthesis, and Luzin approximation. Providence, RI: American Mathematical Society, 2007.
Find full textDomich, P. D. A near-optimal starting solution for polynomial approximation of a continuous function in the Lb1s norm. [Washington, D.C.]: U.S. Dept. of Commerce, National Bureau of Standards, 1986.
Find full textBook chapters on the topic "Approximation of convex function"
Neamtu, Marian. "On Approximation and Interpolation of Convex Functions." In Approximation Theory, Spline Functions and Applications, 411–18. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2634-2_28.
Full textAwan, Muhammad Uzair, Muhammad Aslam Noor, Khalida Inayat Noor, and Themistocles M. Rassias. "Two-Dimensional Trapezium Inequalities via pq-Convex Functions." In Approximation Theory and Analytic Inequalities, 21–34. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60622-0_2.
Full textMennicken, Reinhard. "Perturbations of Semi-Fredholm Operators in Locally Convex Spaces." In Functional Analysis, Holomorphy, and Approximation Theory, 233–304. Boca Raton: CRC Press, 2020. http://dx.doi.org/10.1201/9781003072577-12.
Full textJichang, Kuang. "New Trapezoid Type Inequalities for Generalized Exponentially Strongly Convex Functions." In Approximation Theory and Analytic Inequalities, 273–308. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60622-0_15.
Full textColombeau, J. F., and B. Perrot. "Convolution Equations in Spaces of Polynomials on Locally Convex Spaces." In Functional Analysis, Holomorphy, and Approximation Theory, 21–31. Boca Raton: CRC Press, 2020. http://dx.doi.org/10.1201/9781003072577-3.
Full textKitahara, Kazuaki. "Approximation by vector-valued monotone increasing or convex functions." In Spaces of Approximating Functions with Haar-like Conditions, 58–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0091389.
Full textFox, Kyle, Sungjin Im, Janardhan Kulkarni, and Benjamin Moseley. "Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions." In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 142–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40328-6_11.
Full textGass, Saul I., and Carl M. Harris. "Convex function." In Encyclopedia of Operations Research and Management Science, 147. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_166.
Full textPeterson, James K. "Function Approximation." In Calculus for Cognitive Scientists, 279–99. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-287-874-8_14.
Full textAbe, Shigeo. "Function Approximation." In Support Vector Machines for Pattern Classification, 395–442. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-098-4_11.
Full textConference papers on the topic "Approximation of convex function"
Chickermane, Hemant, and Hae Chang Gea. "Structural Optimization Using a Generalized Convex Approximation." In ASME 1994 Design Technical Conferences collocated with the ASME 1994 International Computers in Engineering Conference and Exhibition and the ASME 1994 8th Annual Database Symposium. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/detc1994-0135.
Full textXu, Yi, Yilin Zhu, Zhongfei Zhang, Yaqing Zhang, and Philip S. Yu. "Convex Approximation to the Integral Mixture Models Using Step Functions." In 2015 IEEE International Conference on Data Mining (ICDM). IEEE, 2015. http://dx.doi.org/10.1109/icdm.2015.48.
Full textAl-Muhja, Malik Saad, Habibulla Akhadkulov, and Nazihah Ahmad. "On weighted approximation of (Co)convex functions with polynomials of varying degrees." In INTERNATIONAL UZBEKISTAN-MALAYSIA CONFERENCE ON “COMPUTATIONAL MODELS AND TECHNOLOGIES (CMT2020)”: CMT2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0059023.
Full textCaruntu, Dumitru I. "On Non-Axisymmetrical Transverse Vibrations of Circular Plates of Convex Parabolic Thickness Variation." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-62020.
Full textDürr, Christoph, Nguyen Kim Thang, Abhinav Srivastav, and Léo Tible. "Non-monotone DR-submodular Maximization over General Convex Sets." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/297.
Full textKumar, Ashok V., and David C. Gossard. "A Sequential Approximation Method for Structural Optimization Using Logarithmic Barriers." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0366.
Full textXiao, Yichi, Zhe Li, Tianbao Yang, and Lijun Zhang. "SVD-free Convex-Concave Approaches for Nuclear Norm Regularization." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/436.
Full textImamoto, Alyson, and Benjamim Tang. "A Recursive Descent Algorithm for Finding the Optimal Minimax Piecewise Linear Approximation of Convex Functions." In Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science (WCECS). IEEE, 2008. http://dx.doi.org/10.1109/wcecs.2008.42.
Full textIvanenko, Yevhen, and Sven Norde. "Approximation of dielectric spectroscopy data with Herglotz functions on the real line and convex optimization." In 2016 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2016. http://dx.doi.org/10.1109/iceaa.2016.7731537.
Full textZhang, Jinhuan, Margaret M. Wiecek, and Wei Chen. "Local Approximation of the Efficient Frontier in Robust Design." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dac-8566.
Full textReports on the topic "Approximation of convex function"
Ward, Rachel A. Reliable Function Approximation and Estimation. Fort Belvoir, VA: Defense Technical Information Center, August 2016. http://dx.doi.org/10.21236/ad1013972.
Full textLin, Daw-Tung, and Judith E. Dayhoff. Network Unfolding Algorithm and Universal Spatiotemporal Function Approximation. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada453011.
Full textTong, C. An Adaptive Derivative-based Method for Function Approximation. Office of Scientific and Technical Information (OSTI), October 2008. http://dx.doi.org/10.2172/945874.
Full textMushtaq, Saima, Mohsan Raza, and Wasim ul Haq. Sufficient Conditions for a Meromorphic Function to Be p-valent Starlike or Convex. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, December 2019. http://dx.doi.org/10.7546/crabs.2019.12.01.
Full textBai, Z. D., C. R. Rao, and L. C. Zhao. MANOVA Type Tests Under a Convex Discrepancy Function for the Standard Multivariate Linear Model. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada271031.
Full textNagayama, Shinobu, Tsutomu Sasao, and Jon T. Butler. Programmable Numerical Function Generators Based on Quadratic Approximation: Architecture and Synthesis Method. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada599939.
Full textPotamianos, Gerasimos, and John Goutsias. Stochastic Simulation Techniques for Partition Function Approximation of Gibbs Random Field Images. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada238611.
Full textLongcope, Donald B. ,. Jr, Thomas Lynn Warren, and Henry Duong. Aft-body loading function for penetrators based on the spherical cavity-expansion approximation. Office of Scientific and Technical Information (OSTI), December 2009. http://dx.doi.org/10.2172/986592.
Full textTang, Ping Tak Peter. Strong uniqueness of best complex Chebyshev approximation to analytic perturbations of analytic function. Office of Scientific and Technical Information (OSTI), March 1988. http://dx.doi.org/10.2172/6357493.
Full textKitago, Masaki, Shunsuke Ehara, and Ichiro Hagiwara. Efficient Construction of Finite Element Model by Implicit Function Approximation of CAD Model. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0127.
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