Results 111 to 120 of about 10,513 (148)
FZC-TDE: The Algorithm for Real-Time Ultrasonic Stress Measurement at Low Sampling Rates. [PDF]
Qiu F +6 more
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A high-resolution database of historical and future climate for Africa developed with deep neural networks. [PDF]
Namiiro SA +4 more
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Surrogate model for statics of fractional thin bar element and its equivalence with mass-spring metamaterial. [PDF]
Szajek K, Sumelka W.
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Local corner smoothing based on deep learning for CNC machine tools. [PDF]
Jiang B +6 more
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Tutorial on Bayesian Functional Regression Using Stan. [PDF]
Jiang Z, Crainiceanu C, Cui E.
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Identification of Regions of Interest in Neuroimaging Data With Irregular Boundary Based on Semiparametric Transformation Models and Interval-Censored Outcomes. [PDF]
Lee CY, Shi H, Ma D, Beg MF, Cao J.
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Multidimensional Spline Approximation
SIAM Journal on Numerical Analysis, 1980Summary: We give direct and inverse estimates for multivariate spline approximation. The direct estimates rest on new results for local polynomial approximation which generalize the work of Brudnyi and Bramble-Hilbert. The inverse estimates are multivariate extensions of one variable ideas.
Dahmen, W., De Vore, R., Scherer, K.
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Nonlinear Nonnested Spline Approximation
Constructive Approximation, 2016Linear and in particular non-linear spline approximation is a most useful tool in the approximation of for instance two-dimensional functions. Usually, piecewise polynomial splines with more and more refined knot-sequences are considered as elements of nested spaces spanned by splines. Generalising from this point of view, it is interesting to consider
Lind, Martin, Petrushev, Pencho
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Biorthogonal Approximation by Splines
Journal of Mathematical Sciences, 2014For bi-infinite grids of points in one dimension on intervals, bi-orthogonal approximations by splines are considered. Explicit expressions for the representation of the splines are derived and specified in detail in the special case of quadratic splines. Error estimated are provided as well in a variety of approaches.
Dem'yanovich, Yu. K., Lebedeva, A. V.
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