Academic literature on the topic 'Gaussian Cubature Formulas'

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Journal articles on the topic "Gaussian Cubature Formulas"

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Lasserre, Jean B. "The existence of Gaussian cubature formulas." Journal of Approximation Theory 164, no. 5 (2012): 572–85. http://dx.doi.org/10.1016/j.jat.2012.01.004.

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Reztsov, A. V. "Nonnegative trigonometric polynomials in many variables and cubature formulas of Gaussian type." Mathematical Notes of the Academy of Sciences of the USSR 50, no. 5 (1991): 1142–46. http://dx.doi.org/10.1007/bf01157701.

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Stepanov, O. A., Yu A. Litvinenko, and A. M. Isaev. "Comparative Analysis of Quasi-Linear Kalman-Type Algorithms in Estimating a Markov Sequence with Nonlinearities in the System and Measurement Equations." Mekhatronika, Avtomatizatsiya, Upravlenie 25, no. 11 (2024): 585–95. http://dx.doi.org/10.17587/mau.25.585-595.

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The so-called Kalman type algorithms (KTA) are considered, among them quasi-linear KTAs introduced as a separate class, the features of which are the Gaussian approximation of the a posteriori probability density function (p.d.f.) at each step and the procedure for processing the current measurement based on the ideology of a linear optimal algorithm. The unified structure of such algorithms and their features are discussed. Two groups are distinguished the quasi-linear KTA: the first is algorithms using Taylor series expansion of the nonlinear functions, and the second is the so-called linear regression KTA. The methods of their designing are considered, and the common features are described. Detailed attention is paid to the following KTAs: the extended Kalman filter (EKF), polynomial filters of the second and third order (PF2 and PF3), as representatives of the first group, and the Unscented and Cubature Kalman filters (UKF and CKF), as representatives the second one. Their comparative analysis is carried out using the estimation problem of a scalar Markov sequence in the presence of nonlinearities in the shaping filter and in the measurement equations. For all the studied algorithms, the formulas are given in a form convenient for comparison. Based on these formulas, possible causes of a decrease in accuracy and a violation of the consistency properties are identified. Using the previously proposed procedure based on the method of statistical tests, predictive simulation was carried out, which made it possible to confirm the conclusions obtained previously on the basis of an analysis of the formulas for the algorithms being compared. The simulation also allowed to compare the computational complexity of the compared algorithms. The results of the study may be useful to developers involved in the processing of measurement information when choosing a filtering algorithm for solving specific practical estimation problems.
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Bannai, Eiichi, Etsuko Bannai, Masatake Hirao та Masanori Sawa. "On the existence of minimum cubature formulas for Gaussian measure on ℝ2 of degree t supported by $[\frac{t}{4}]+1$ circles". Journal of Algebraic Combinatorics 35, № 1 (2011): 109–19. http://dx.doi.org/10.1007/s10801-011-0295-3.

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Berens, H., H. J. Schmid, and Y. Xu. "Multivariate Gaussian cubature formulae." Archiv der Mathematik 64, no. 1 (1995): 26–32. http://dx.doi.org/10.1007/bf01193547.

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Schmid, H. J., and Yuan Xu. "On bivariate Gaussian cubature formulae." Proceedings of the American Mathematical Society 122, no. 3 (1994): 833. http://dx.doi.org/10.1090/s0002-9939-1994-1209428-0.

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Wang, Tianjing, Lanyong Zhang, and Sheng Liu. "Improved Robust High-Degree Cubature Kalman Filter Based on Novel Cubature Formula and Maximum Correntropy Criterion with Application to Surface Target Tracking." Journal of Marine Science and Engineering 10, no. 8 (2022): 1070. http://dx.doi.org/10.3390/jmse10081070.

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Robust nonlinear filtering is an important method for tracking maneuvering targets in non-Gaussian noise environments. Although there are many robust filters for nonlinear systems, few of them have ideal performance for mixed Gaussian noise and non-Gaussian noise (such as scattering noise) in practical applications. Therefore, a novel cubature formula and maximum correntropy criterion (MCC)-based robust cubature Kalman filter is proposed. First, the fully symmetric cubature criterion and high-order divided difference are used to construct a new fifth-degree cubature formula using fewer symmetric cubature points. Then, a new cost function is obtained by combining the weighted least-squares method and the MCC loss criterion to deal with the abnormal values of non-Gaussian noise, which enhances the robustness; and statistical linearization methods are used to calculate the approximate result of the measurement process. Thus, the final fifth-degree divided difference–maximum correntropy cubature Kalman filter (DD-MCCKF) framework is constructed. A typical surface-maneuvering target-tracking simulation example is used to verify the tracking accuracy and robustness of the proposed filter. Experimental results indicate that the proposed filter has a higher tracking accuracy and better numerical stability than other common nonlinear filters in non-Gaussian noise environments with fewer cubature points used.
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Jandrlic, Davorka, Miodrag Spalevic, and Jelena Tomanovic. "Error estimates for certain cubature formulae." Filomat 32, no. 20 (2018): 6893–902. http://dx.doi.org/10.2298/fil1820893j.

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We estimate the errors of selected cubature formulae constructed by the product of Gauss quadrature rules. The cases of multiple and (hyper-)surface integrals over n-dimensional cube, simplex, sphere and ball are considered. The error estimates are obtained as the absolute value of the difference between cubature formula constructed by the product of Gauss quadrature rules and cubature formula constructed by the product of corresponding Gauss-Kronrod or corresponding generalized averaged Gaussian quadrature rules. Generalized averaged Gaussian quadrature rule ?2l+1 is (2l + 1)-point quadrature formula. It has 2l + 1 nodes and the nodes of the corresponding Gauss rule Gl with l nodes form a subset, similar to the situation for the (2l + 1)-point Gauss-Kronrod rule H2l+1 associated with Gl. The advantages of bG2l+1 are that it exists also when H2l+1 does not, and that the numerical construction of ?2l+1, based on recently proposed effective numerical procedure, is simpler than the construction of H2l+1.
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Bojanov, Borislav D., and Dimitar K. Dimitrov. "Gaussian extended cubature formulae for polyharmonic functions." Mathematics of Computation 70, no. 234 (2000): 671–84. http://dx.doi.org/10.1090/s0025-5718-00-01206-0.

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Orive, Ramón, Juan C. Santos-León, and Miodrag M. Spalević. "Cubature formulae for the Gaussian weight. Some old and new rules." ETNA - Electronic Transactions on Numerical Analysis 53 (2020): 426–38. http://dx.doi.org/10.1553/etna_vol53s426.

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Dissertations / Theses on the topic "Gaussian Cubature Formulas"

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Niime, Fabio Nosse [UNESP]. "Polinômios ortogonais em várias variáveis." Universidade Estadual Paulista (UNESP), 2011. http://hdl.handle.net/11449/86506.

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Made available in DSpace on 2014-06-11T19:22:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-02-24Bitstream added on 2014-06-13T20:28:32Z : No. of bitstreams: 1 niime_fn_me_sjrp.pdf: 457352 bytes, checksum: 318f01064234c003baca33cae4183d6d (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>O objetivo des trabalho é estudar os polinômios ortogonais em várias variáveis com relação a um funcional linear, L e suas propriedades análogas às dos polinômios ortogonais em uma variável, tais como: a relação de três termos, a relação de recorrência de três termos, o teorema de Favard, os zeros comuns ea cubatura gaussiana. Além disso, apresentamos um método para gerar polinômios ortonormais em duas variáveis e alguns exemplos.<br>The aim here is to study the orthogonal polynomials in several variables with respect to a linear functional, L. also, to study its properties analogous to orthogonal polynomials in one variable, such as the theree term relation, the three term recurrence relation, Favard's theorem, the common zeros and Gaussian cubature. A method to generating orthonormal polynomials in two variables and some examples are presented.
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Book chapters on the topic "Gaussian Cubature Formulas"

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Cuyt, Annie, Brahim Benouahmane, and Brigitte Verdonk. "Spherical Orthogonal Polynomials and Symbolic-Numeric Gaussian Cubature Formulas." In Computational Science - ICCS 2004. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24687-9_71.

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