Results 91 to 100 of about 1,054,196 (331)

A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation

open access: yes, 2008
For high dimensional problems, such as approximation and integration, one cannot afford to sample on a grid because of the curse of dimensionality. An attractive alternative is to sample on a low discrepancy set, such as an integration lattice or a ...
Dick, Josef   +2 more
core   +1 more source

Multivariate Refinable Interpolating Functions

open access: yesApplied and Computational Harmonic Analysis, 1999
The author gives an algorithm for the construction of refinable interpolating functions for an arbitrary dilation matrix. This construction of refinable interpolating functions is an intermediate step in the construction of orthonormal wavelet bases and is of interest in its own right.
openaire   +3 more sources

Adsorption and Separation by Flexible MOFs

open access: yesAdvanced Materials, EarlyView.
Flexible metal–organic frameworks (MOFs) present significant potential for gas storage and separation due to their structural dynamic. This review explores the rationale behind the flexible MOFs' enhanced working capacity and separation factors. It also addresses key challenges, including phase transition kinetics, crystal robustness, cycling, shaping,
Irena Senkovska   +4 more
wiley   +1 more source

Advancements in Understanding the Physicochemical Properties of Reticular Materials: An In Situ and Operando Spectroscopic Perspective

open access: yesAdvanced Materials, EarlyView.
This review explores how in situ and operando spectroscopic techniques reveal the real‐time behavior of reticular materials, including MOFs and COFs. These methods track material formation and functionalization, structural changes, defect formation, dynamic responses to external triggers, and catalytic processes.
Bettina Baumgartner   +4 more
wiley   +1 more source

Integrating Interpolation and Extrapolation: A Hybrid Predictive Framework for Supervised Learning

open access: yesApplied Sciences
In the domain of supervised learning, interpolation and extrapolation serve as crucial methodologies for predicting data points within and beyond the confines of a given dataset, respectively. The efficacy of these methods is closely linked to the nature
Bo Jiang   +4 more
doaj   +1 more source

Fast systematic encoding of multiplicity codes [PDF]

open access: yes, 2017
We present quasi-linear time systematic encoding algorithms for multiplicity codes. The algorithms have their origins in the fast multivariate interpolation and evaluation algorithms of van der Hoeven and Schost (2013), which we generalise to address ...
Coxon, Nicholas
core   +2 more sources

Partition of Unity Interpolation on Multivariate Convex Domains

open access: yes, 2014
In this paper we present a new algorithm for multivariate interpolation of scattered data sets lying in convex domains $\Omega \subseteq \RR^N$, for any $N \geq 2$.
Cavoretto, Roberto   +2 more
core   +1 more source

The proper interpolation space for multivariate Birkhoff interpolation

open access: yesJournal of Computational and Applied Mathematics, 2011
AbstractMultivariate Birkhoff interpolation problem has many important applications, such as in finite element method. In this paper two algorithms are given to compute the basis of the minimal interpolation space and the lower interpolation space respectively for an arbitrary given node set and the corresponding interpolation conditions on each node ...
Junjie Chai, Ying Li, Na Lei, Peng Xia
openaire   +2 more sources

PiP‐Plex: A Particle‐in‐Particle System for Multiplexed Quantification of Proteins Secreted by Single Cells

open access: yesAdvanced Materials, EarlyView.
Detecting proteins secreted by a single cell while retaining its viability remains challenging. A particles‐in‐particle (PiPs) system made by co‐encapsulating barcoded microparticles (BMPs) with a single cell inside an alginate hydrogel particle is introduced.
Félix Lussier   +10 more
wiley   +1 more source

Multivariate Smooth Symmetrized and Perturbed Hyperbolic Tangent Neural Network Approximation over Infinite Domains

open access: yesMathematics
In this article, we study the multivariate quantitative smooth approximation under differentiation of functions. The approximators here are multivariate neural network operators activated by the symmetrized and perturbed hyperbolic tangent activation ...
George A. Anastassiou
doaj   +1 more source

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