scholarly journals Weak endpoint bounds for matrix weights

2020 ◽  
Author(s):  
David Cruz-Uribe ◽  
Joshua Isralowitz ◽  
Kabe Moen ◽  
Sandra Pott ◽  
Israel Rivera-Ríos
Keyword(s):  
Matrix Weights

Universal modification of vector weighted method of correlated sampling with finite computational cost

2019 ◽  
Vol 34 (1) ◽  
pp. 43-55
Author(s):  
Ilya N. Medvedev
Keyword(s):  
Markov Chain ◽  
Integral Equations ◽  
Numerical Experiments ◽  
Radiation Transfer ◽  
Computational Cost ◽  
Linear Functionals ◽  
Weighted Estimator ◽  
Matrix Weights ◽  
Correlated Sampling

Abstract The weighted method of dependent trials or weighted method of correlated sampling (MCS) allows one to construct estimators for functionals based on the same Markov chain simultaneously for a given range of the problem parameters. Choosing an appropriate Markov chain, it is necessary to take into account additional conditions providing the finiteness of the computational cost of weighted MCS. In this paper we study the issue of finite computational cost of the method of correlated sampling (MCS) in application to evaluation of linear functionals of solutions to a set of systems of 2nd kind integral equations. A universal modification of the vector weighted MCS is constructed providing the branching of chain trajectory according to elements of matrix weights. It is proved that the computational cost of the constructed algorithm is bounded in the case the base functionals are also bounded. The results of numerical experiments using the modified weighted estimator are presented for some problems of the theory of radiation transfer subject to polarization.

scholarly journals EVALUATING THE PERFORMANCE OF COLOMBIAN BANKS BY HYBRID MULTICRITERIA DECISION MAKING METHODS

2020 ◽  
Vol 21 (6) ◽  
pp. 1707-1730
Author(s):  
Amir Karbassi Yazdi ◽  
Thomas Hanne ◽  
Juan Carlos Osorio Gómez
Keyword(s):  
Decision Making ◽  
Balanced Scorecard ◽  
Service Sector ◽  
Banking Sector ◽  
Multicriteria Decision Making ◽  
Evaluation Process ◽  
Decision Matrix ◽  
Multicriteria Decision ◽  
Strategic Issues ◽  
Matrix Weights

The aim of the study in this paper is to show how the performance of banks can be evaluated by ranking them based on Balanced Scorecard (BSC) and Multicriteria Decision Making (MCDM) methods. Nowadays, assessing the performance of companies is a vital work for finding their weaknesses and strengths. The banking sector is an important area in the service sector. Many people want to know which bank performs best when entrusting their money to them. For assessing the performance of banks, BSC can be used. This method helps to translate strategic issues to meaningful insights for the respective financial institutions. After that, the banks will be ranked based on performance indicators by the Weighted Aggregated Sum Product Assessment (WASPAS) method. Because this method is based on a decision matrix, weights are required. To find such weights, the Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. The results show that the International Bank of Colombia has a much better performance than other Colombian banks. Besides, further insights regarding the evaluation process based on BSC, SWARA, and WASPAS are obtained.

scholarly journals Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 661 ◽  
Author(s):  
Allegra Conti ◽  
Andrea Duggento ◽  
Maria Guerrisi ◽  
Luca Passamonti ◽  
Iole Indovina ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Mri ◽  
Pearson Correlation ◽  
Related Information ◽  
Matrix Weights ◽  
Graph Metrics ◽  
Large N ◽  
Subject Variability ◽  
Key Factor ◽  
Global And Local

A growing number of studies are focusing on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, it is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing the inter- and intra-subject variability of connectivity matrices, as well as graph-theoretical measures, in a large (n = 1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected, as opposed to directed, methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra-subject variabilities in both directed and undirected connectomic measures.

scholarly journals Reducibility of matrix weights

2016 ◽  
Vol 45 (2) ◽  
pp. 349-374 ◽  
Author(s):  
Juan Tirao ◽  
Ignacio Zurrián
Keyword(s):  
Matrix Weights

scholarly journals Summation of Multiple Fourier Series in Matrix Weighted -Spaces

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Morten Nielsen
Keyword(s):  
Fourier Series ◽  
Weighted Space ◽  
Multiple Fourier Series ◽  
Weighted Spaces ◽  
Partial Sums ◽  
Summation Methods ◽  
Matrix Weights ◽  
Muckenhoupt Condition ◽  
Jackson Kernel

This paper is concerned with rectangular summation of multiple Fourier series in matrix weighted -spaces. We introduce a product Muckenhoupt condition for matrix weights and prove that rectangular Fourier partial sums converge in the corresponding matrix weighted space , , if and only if the weight satisfies the product Muckenhoupt condition. The same result is shown to hold true for other summation methods such as Cesàro and summation with the Jackson kernel.

scholarly journals Convex body domination and weighted estimates with matrix weights

2017 ◽  
Vol 318 ◽  
pp. 279-306 ◽  
Author(s):  
Fedor Nazarov ◽  
Stefanie Petermichl ◽  
Sergei Treil ◽  
Alexander Volberg
Keyword(s):  
Convex Body ◽  
Weighted Estimates ◽  
Matrix Weights

scholarly journals A New Algorithm for System of Integral Equations

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Abdujabar Rasulov ◽  
Adem Kilicman ◽  
Zainidin Eshkuvatov ◽  
Gulnora Raimova
Keyword(s):  
Computational Complexity ◽  
Boundary Value Problem ◽  
Integral Equations ◽  
Parabolic Equations ◽  
Initial Boundary ◽  
Initial Boundary Value Problem ◽  
System Of Integral Equations ◽  
Matrix Weights ◽  
System Of Parabolic Equations ◽  
Initial Boundary Value

We develop a new algorithm to solve the system of integral equations. In this new method no need to use matrix weights. Beacause of it, we reduce computational complexity considerable. Using the new algorithm it is also possible to solve an initial boundary value problem for system of parabolic equations. To verify the efficiency, the results of computational experiments are given.

Sign in / Sign up

Export Citation Format

Share Document