Results 121 to 130 of about 71,879 (309)
Journal of Inequalities and Applications, 2010 Let denote the sequence of polynomials orthogonal with respect to the non-discrete Sobolev inner product , where and with , . In this paper, we prove a Cohen type inequality for the Fourier expansion in terms of the orthogonal polynomials ...
Marcellán Francisco +1 more
doaj
Projection formulas for orthogonal polynomials of a discrete variable
Journal of Mathematical Analysis and Applications, 1974 have important applications to the theory of orthogonal polynomials. For most of the applications of (1.1) and (1.2) mentioned in these papers, one does not need to have explicit formulas for the kernels (measures and coefficients, respectively) since only their non-negativity was needed. By concentrating on the special case in which &(x) and qn( x are
openaire +2 more sources
Quarterly Journal of the Royal Meteorological Society, EarlyView.We study the impact of observation‐error correlations in data assimilation using both a simple idealised system and a more realistic configuration. A spectral analysis of data assimilation in the idealised system allows us to gain insights on the effect of observation‐error correlations, which are then validated using the realistic configuration.
Olivier Goux +4 more
wiley +1 more source
Some multivariable orthogonal polynomials of the Askey tableau-discrete families [PDF]
, 1991 M. V. Tratnik
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Quarterly Journal of the Royal Meteorological Society, EarlyView.We present a compatible finite‐element discretisation of a general formulation of moist shallow‐water equations, with the aim of providing a simple model to advance understanding of physics–dynamics coupling. We detail set‐ups and show three moist shallow‐water test cases in four different model formulations. The results demonstrate differences between
Nell Hartney +2 more
wiley +1 more source
Statistical Complexity of Quantum Learning
Advanced Quantum Technologies, EarlyView.The statistical performance of quantum learning is investigated as a function of the number of training data N$N$, and of the number of copies available for each quantum state in the training and testing data sets, respectively S$S$ and V$V$. Indeed, the biggest difference in quantum learning comes from the destructive nature of quantum measurements ...
Leonardo Banchi +3 more
wiley +1 more source
, 2002 We compute the pointwise asymptotics of orthogonal polynomials with respect to a general class of pure point measures supported on finite sets as both the number of nodes of the measure and also the degree of the orthogonal polynomials become large.
Baik, Jinho +3 more
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Robustness assessment of reinforced concrete structures for different failure scenarios
Structural Concrete, EarlyView.Abstract This study describes the robustness assessment of 3D reinforced concrete structures analyzing the response of the 2D frames in different design configurations and failure scenarios. The structures are characterized by both frames with wide beams and seismic‐resistant frames with deep beams.
E. Miceli +2 more
wiley +1 more source
Applications of Artificial Intelligence in Neurological Voice Disorders
World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.ABSTRACT Neurological voice disorders, such as Parkinson's disease, laryngeal dystonia, and stroke‐induced dysarthria, significantly impact speech production and communication. Traditional diagnostic methods rely on subjective assessment, whereas artificial intelligence (AI) offers objective, noninvasive, and scalable solutions for voice analysis. This
Dongren Yao +2 more
wiley +1 more source
DCKTKT: A New Discrete Cosine-Krawtchouk-Tchebichef Transform
Journal of EngineeringReal-world signals are often intricate and difficult to analyze. Therefore, to facilitate the analysis of signal components, the researchers represent the signal in different domains (transform domain), providing a new perspective and offering ...
Mariam Taha Yaseen +1 more
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