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Relevant bibliographies by topics / Spline methods

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Academic literature on the topic 'Spline methods'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Spline methods"

1

Kuželka, K., and R. Marušák. "Use of nonparametric regression methods for developing a local stem form model." Journal of Forest Science 60, No. 11 (2014): 464–71. http://dx.doi.org/10.17221/56/2014-jfs.

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A local mean stem curve of spruce was represented using regression splines. Abilities of smoothing spline and P-spline to model the mean stem curve were evaluated using data of 85 carefully measured stems of Norway spruce. For both techniques the optimal amount of smoothing was investigated in dependence on the number of training stems using a cross-validation method. Representatives of main groups of parametric models &ndash; single models, segmented models and models with variable coefficient &ndash; were compared with spline models using five statistic criteria. Both regression spli

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2

Boehm, Wolfgang. "Multivariate spline methods in CAGD." Computer-Aided Design 18, no. 2 (1986): 102–4. http://dx.doi.org/10.1016/0010-4485(86)90158-2.

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Wang, Bin, Wenzhong Shi, and Zelang Miao. "Comparative Analysis for Robust Penalized Spline Smoothing Methods." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/642475.

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Smoothing noisy data is commonly encountered in engineering domain, and currently robust penalized regression spline models are perceived to be the most promising methods for coping with this issue, due to their flexibilities in capturing the nonlinear trends in the data and effectively alleviating the disturbance from the outliers. Against such a background, this paper conducts a thoroughly comparative analysis of two popular robust smoothing techniques, theM-type estimator andS-estimation for penalized regression splines, both of which are reelaborated starting from their origins, with their

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Buffa, A., G. Sangalli, and R. Vázquez. "Isogeometric methods for computational electromagnetics: B-spline and T-spline discretizations." Journal of Computational Physics 257 (January 2014): 1291–320. http://dx.doi.org/10.1016/j.jcp.2013.08.015.

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da Veiga, L. Beirão, A. Buffa, G. Sangalli, and R. Vázquez. "Mathematical analysis of variational isogeometric methods." Acta Numerica 23 (May 2014): 157–287. http://dx.doi.org/10.1017/s096249291400004x.

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This review paper collects several results that form part of the theoretical foundation of isogeometric methods. We analyse variational techniques for the numerical resolution of PDEs based on splines or NURBS and we provide optimal approximation and error estimates in several cases of interest. The theory presented also includes estimates for T-splines, which are an extension of splines allowing for local refinement. In particular, we focus our attention on elliptic and saddle point problems, and we define spline edge and face elements. Our theoretical results are demonstrated by a rich set o

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Sapidis, N. "Methods of Shape-Preserving Spline Approximation." Computer-Aided Design 33, no. 10 (2001): 747–48. http://dx.doi.org/10.1016/s0010-4485(01)00062-8.

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Grigorieff, R. D., and I. H. Solan. "Spline petrov-galerkin methods with quadrature." Numerical Functional Analysis and Optimization 17, no. 7-8 (1996): 755–84. http://dx.doi.org/10.1080/01630569608816723.

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Botella, Olivier, and Karim Shariff. "B-spline Methods in Fluid Dynamics." International Journal of Computational Fluid Dynamics 17, no. 2 (2003): 133–49. http://dx.doi.org/10.1080/1061856031000104879.

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Roch, Steffen. "Spline Approximation Methods Cutting Off Singularities." Zeitschrift für Analysis und ihre Anwendungen 13, no. 2 (1994): 329–45. http://dx.doi.org/10.4171/zaa/510.

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Yuyukin, Igor V. "GEOID APPROXIMATION BY SPLINE FUNCTIONS METHODS." Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 12, no. 2 (2020): 262–71. http://dx.doi.org/10.21821/2309-5180-2020-12-2-262-271.

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Dissertations / Theses on the topic "Spline methods"

1

Welham, Suzanne Jane. "Smoothing spline methods within the mixed model framework." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425673.

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Gutting, Martin. "Fast multipole methods for oblique derivative problems." Aachen Shaker, 2007. http://d-nb.info/988919346/04.

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Kaya, Hikmet Emre. "A comparative study between the cubic spline and b-spline interpolation methods in free energy calculations." Master's thesis, Faculty of Science, 2020. http://hdl.handle.net/11427/32228.

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Numerical methods are essential in computational science, as analytic calculations for large datasets are impractical. Using numerical methods, one can approximate the problem to solve it with basic arithmetic operations. Interpolation is a commonly-used method, inter alia, constructing the value of new data points within an interval of known data points. Furthermore, polynomial interpolation with a sufficiently high degree can make the data set differentiable. One consequence of using high-degree polynomials is the oscillatory behaviour towards the endpoints, also known as Runge's Phenomenon.

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Ng, Kit Sung. "Quadratic spline collocation methods for systems of elliptic PDEs." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0024/MQ50355.pdf.

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Wang, Hongrui. "Error and stability analysis for B-spline finite element methods." Thesis, University of Strathclyde, 2015. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=26570.

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The thesis studies the approximation properties of splines with maximum smoothness. We are interested in the behaviour of the approximation as the degree of the spline increases (so does its smoothness). By studying B-spline interpolation, we obtain error estimates measured in the semi-norm that are explicit in terms of mesh size, degree and smoothness. This new result also gives a higher approximation order than existing estimations. With the results, we investigate the B-spline finite element approximation with k-refinement, which is a strategy of improving the accuracy by increasing the deg

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Kim, Heeyoung. "Statistical methods for function estimation and classification." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/44806.

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This thesis consists of three chapters. The first chapter focuses on adaptive smoothing splines for fitting functions with varying roughness. In the first part of the first chapter, we study an asymptotically optimal procedure to choose the value of a discretized version of the variable smoothing parameter in adaptive smoothing splines. With the choice given by the multivariate version of the generalized cross validation, the resulting adaptive smoothing spline estimator is shown to be consistent and asymptotically optimal under some general conditions. In the second part, we derive the asympt

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Zhu, Ying. "Quartic-spline collocation methods for fourth-order two-point boundary value problems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ58780.pdf.

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Tsao, Su-Ching 1961. "Evaluation of drug absorption by cubic spline and numerical deconvolution." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/276954.

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A novel approach using smoothing cubic splines and point-area deconvolution to estimate the absorption kinetics of linear systems has been investigated. A smoothing cubic spline is employed as an interpolation function since it is superior to polynomials and other functions commonly used for representation of empirical data in several aspects. An advantage of the method is that results obtained from the same data set will be more consistent, irrespective of who runs the program or how many times you run it. In addition, no initial estimates are needed to run the program. The same sampling time

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O'Bannon, Terry Robert. "A comparison of interpolative methods for cell mapping analyses of nonlinear systems." Thesis, Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/16394.

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Berkel, Paula. "Multiscale methods for the combined inversion of normal mode and gravity variations." Aachen Shaker, 2009. http://d-nb.info/997085304/04.

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Books on the topic "Spline methods"

1

Spline functions: Computational methods. Society for Industrial and Applied Mathematics, 2015.

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Computational methods for algebraic spline surfaces. Springer, 2005.

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R, Cormier David, ed. Spline regression models. Sage Publications, 2002.

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Averbuch, Amir Z., Pekka Neittaanmäki, and Valery A. Zheludev. Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-22303-2.

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Averbuch, Amir Z., Pekka Neittaanmäki, and Valery A. Zheludev. Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92123-5.

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Averbuch, Amir Z., Pekka Neittaanmaki, and Valery A. Zheludev. Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-8926-4.

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Schiesser, William E. Spline Collocation Methods for Partial Differential Equations. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119301066.

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Splines and variational methods. Wiley, 1989.

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9

Prenter, P. M. Splines and variational methods. Dover Publications, 2008.

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Smoothing splines: Methods and applications. CRC Press, 2011.

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Book chapters on the topic "Spline methods"

1

Saranen, Jukka, and Gennadi Vainikko. "Spline Approximation Methods." In Springer Monographs in Mathematics. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04796-5_13.

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Freeden, Willi, and Martin Gutting. "Spline Exact Integration." In Integration and Cubature Methods. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315195674-14.

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Freeden, Willi, and Martin Gutting. "Algebraic Spline Integration." In Integration and Cubature Methods. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315195674-3.

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Freeden, Willi, and Martin Gutting. "Periodic Spline Integration." In Integration and Cubature Methods. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315195674-5.

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Wakefield, Jon. "Spline and Kernel Methods." In Springer Series in Statistics. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0925-1_11.

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Singh, Dhananjay, Madhusudan Singh, and Zaynidinov Hakimjon. "Evaluation Methods of Spline." In Signal Processing Applications Using Multidimensional Polynomial Splines. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2239-6_5.

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Berghaus, Donald. "The Smoothed Spline." In Numerical Methods for Experimental Mechanics. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1473-2_3.

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Strelkovskaya, I., I. Solovskaya, and J. Strelkovska. "Spline-Approximation and Spline-Extrapolation Methods in Telecommunication Problems." In Current Trends in Communication and Information Technologies. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76343-5_1.

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Bratlie, Jostein, Rune Dalmo, and Børre Bang. "Wavelet Compression of Spline Coefficients." In Numerical Methods and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15585-2_27.

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Averbuch, Amir Z., Pekka Neittaanmäki, and Valery A. Zheludev. "Polynomial Spline-Wavelets." In Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22303-2_8.

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Conference papers on the topic "Spline methods"

1

Bajaj, Chandrajit, Radhakrishna Bettadapura, Na Lei, Alex Mollere, Chao Peng, and Alexander Rand. "Constructing A-spline weight functions for stable WEB-spline finite element methods." In the 14th ACM Symposium. ACM Press, 2010. http://dx.doi.org/10.1145/1839778.1839800.

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Semenova, K. I., and F. J. Yanovsky. "Spline models for synthetic aperture radar application." In 2012 International Conference on Mathematical Methods in Electromagnetic Theory (MMET). IEEE, 2012. http://dx.doi.org/10.1109/mmet.2012.6331255.

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Zakaria, Nur Fateha, Nuraini Abu Hassan, Nur Nadiah Abd Hamid, Ahmad Abd Majid, and Ahmad Izani Md Ismail. "Solving Boussinesq equation using quintic B-spline and quintic trigonometric B-spline interpolation methods." In THE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES: Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society. Author(s), 2017. http://dx.doi.org/10.1063/1.4980904.

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Chanthrasuwan, Maveeka, Nur Asreenawaty Mohd Asri, Nur Nadiah Abd Hamid, Ahmad Abd Majid, and Amirah Azmi. "Solving Buckmaster equation using cubic B-spline and cubic trigonometric B-spline collocation methods." In PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation. Author(s), 2017. http://dx.doi.org/10.1063/1.4995859.

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Anuar, Hanis Safirah Saiful, Nur Hidayah Mafazi, Nur Nadiah Abd Hamid, Ahmad Abd Majid, and Amirah Azmi. "Solving Dym equation using quartic B-spline and quartic trigonometric B-spline collocation methods." In PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation. Author(s), 2017. http://dx.doi.org/10.1063/1.4995860.

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Tsutahara, Michihisa, Akira Miura, Kazuhiko Ogawa, and Katsuhiko Akita. "Three-dimensional Vortex Method Using the Ferguson Spline." In Selected Papers of the First International Conference on Vortex Methods. WORLD SCIENTIFIC, 2000. http://dx.doi.org/10.1142/9789812793232_0018.

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Zhang, Yong, Li-Bin Liu, and Huai-Huo Cao. "Parametric Cubic Spline Methods for Solving Hyperbolic Equations." In 2010 2nd International Conference on Information Engineering and Computer Science (ICIECS). IEEE, 2010. http://dx.doi.org/10.1109/iciecs.2010.5678338.

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Pehnec, Igor, Damir Vucina, and Frane Vlak. "EVOLUTIONARY TOPOLOGY OPIMIZATION USING PARAMETERIZED B-SPLINE SURFACE." In VII European Congress on Computational Methods in Applied Sciences and Engineering. Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2016. http://dx.doi.org/10.7712/100016.2413.7315.

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de Gelder, Erwin, Elisabeth Brunner, Cornelis C. de Visser, and Michel Verhaegen. "Filtering and Identification for Spline based Wavefront Reconstruction from Gradient Measurements in Adaptive Optics." In Adaptive Optics: Analysis, Methods & Systems. OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.aow3f.4.

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Mazzia, Francesca, Alessandra Sestini, and Donato Trigiante. "BS Methods: A New Class of Spline Collocation BVMs." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: International Conference on Numerical Analysis and Applied Mathematics 2008. American Institute of Physics, 2008. http://dx.doi.org/10.1063/1.2991076.

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Reports on the topic "Spline methods"

1

Chui, Charles K. Multivariate Regression with Emphasis on Multivariate Spline Methods. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada197793.

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Williams, Daniel A., and Louise A. Raphael. Wavelets and Splines in Numerical Methods and Compression. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada294986.

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Manke, J. A tensor product B-spline method for numerical grid generation. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/5005256.

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Manke, J. A tensor product b-spline method for 3D multi-block elliptic grid generation. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/5536897.

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Castillo, Victor Manuel. Cubic Spline Collocation Method for the Simulation of Turbulent Thermal Convection in Compressible Fluids. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/15014452.

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Friedman, A., and E. Sonnendrucker. Some Aspects of Non-Split Vlasov Simulation Methods. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/15002126.

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Ajeesh, S. S., and Jayachandran S. Arul. ELASTIC BUCKLING OF COLD-FORMED STEEL COMPLEX CROSS SECTIONS USING CONSTRAINED SPLINE FINITE STRIP METHOD (CSFSM). The Hong Kong Institute of Steel Construction, 2018. http://dx.doi.org/10.18057/icass2018.p.147.

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Li, Xin, Eric L. Miller, Carey Rappaport, and Michael Silevich. An Adaptive B-Spline Method for Low-order Image Reconstruction Problems - Final Report - 09/24/1997 - 09/24/2000. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/791462.

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Pousin, Jerome G., Habib N. Najm, and Philippe Pierre Pebay. A half-explicit, non-split projection method for low Mach number flows. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/919179.

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Rasmussen, Jeffrey L. Evaluation of Bootstrap and Parametric Percentile Contrasts. Volume 1. Splits Analysis: A Method for Noncentral Tendency Comparisons. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada230506.

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