Results 31 to 40 of about 5,235,033 (372)
Lagrange Multivariate Polynomial Interpolation: A Random Algorithmic Approach
Journal of Applied Mathematics, 2022 The problems of polynomial interpolation with several variables present more difficulties than those of one-dimensional interpolation. The first problem is to study the regularity of the interpolation schemes.
A. Essanhaji, M. Errachid
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Interpolation of Gentle Spaces [PDF]
Abstract and Applied Analysis, 2014 The notion of gentle spaces, introduced by Jaffard, describes what would be an “ideal” function space to work with wavelet coefficients. It is based mainly on the separability, the existence of bases, the homogeneity, and theγ-stability. We prove that real and complex interpolation spaces between two gentle spaces are also gentle.
Ben Slimane, Mourad, Ben Braiek, Hnia
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The problem of trigonometric Fourier series multipliers of classes in λp,q spaces
Қарағанды университетінің хабаршысы. Математика сериясы, 2020 In this article, we consider weighted spaces of numerical sequences λp,q, which are defined as sets of sequences a = {ak}∞k=1, for which the norm ||a||λp,q := (∞Σk=1|ak|qkq/p −1)1/q < ∞ is finite. In the case of non-increasing sequences, the norm of the
A. Bakhyt, N.T. Tleukhanova
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Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2020 In this paper, we explore the space-time video super-resolution task, which aims to generate a high-resolution (HR) slow-motion video from a low frame rate (LFR), low-resolution (LR) video. A simple solution is to split it into two sub-tasks: video frame
Xiaoyu Xiang +5 more
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International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
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Comparison of Different Approaches to Define the Applicability Domain of QSAR Models
Molecules, 2012 One of the OECD principles for model validation requires defining the Applicability Domain (AD) for the QSAR models. This is important since the reliable predictions are generally limited to query chemicals structurally similar to the training compounds ...
Roberto Todeschini +5 more
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Geodesic Learning With Uniform Interpolation on Data Manifold
IEEE Access, 2022 Recently with the development of deep learning on data representation and generation, how to sampling on a data manifold becomes a crucial problem for research.
Cong Geng +3 more
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Magnetic Resonance in Medicine, 2018 To develop an improved k‐space reconstruction method using scan‐specific deep learning that is trained on autocalibration signal (ACS) data.
M. Akçakaya +3 more
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Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
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A Hybrid Method for Interpolating Missing Data in Heterogeneous Spatio-Temporal Datasets
ISPRS International Journal of Geo-Information, 2016 Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly developed
Min Deng +3 more
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