Results 31 to 40 of about 261,453 (169)
On the acceleration of convergence by regular matrix methods; pp. 3–17 [PDF]
Proceedings of the Estonian Academy of Sciences, 2008 Regular matrix methods that improve and accelerate the convergence of sequences and series are studied. Some problems related to the speed of convergence of sequences and series with respect to matrix methods are discussed.
Ants Aasma
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International Journal of Mathematics and Mathematical Sciences, 1997 King[3] introduced and examined the concepts of almost A-summable sequence, almost conservative matrix and almost regular matrix By following King, in this paper we introduce and examine the concepts of θ-almost A-summable sequence, θ-almost conservative
Fatih Nuray
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Matrix Regularization for Gauge Theories
Progress of Theoretical and Experimental PhysicsAbstract We consider how gauge theories can be described by matrix models. Conventional matrix regularization is defined for scalar functions and is not applicable to gauge fields, which are connections of fiber bundles. We clarify how the degrees of freedom of gauge fields are related to the matrix degrees of freedom, by formulating the
Hiroyuki Adachi +2 more
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Constructive Regularization of the Random Matrix Norm [PDF]
Journal of Theoretical Probability, 2019 We show a simple local norm regularization algorithm that works with high probability. Namely, we prove that if the entries of a $n \times n$ matrix $A$ are i.i.d. symmetrically distributed and have finite second moment, it is enough to zero out a small fraction of the rows and columns of $A$ with largest $L_2$ norms in order to bring the operator norm
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On the spectra of reduced distance matrix of dendrimers [PDF]
Transactions on Combinatorics, 2013 Let G be a simple connected graph and {v_1,v_2,... , v_k} be the set of pendent (vertices of degree one) vertices of G. The reduced distance matrix of G is an square matrix whose (i,j)-entry is the topological distance between v_i and v_j of G.
Abbas Heydari
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Matrix Regular Operator Spaces
Journal of Functional Analysis, 1998 A norm on an ordered real Banach space \(E\) is called regular (or Riesz norm) if \(-x\leq y\leq x\) implies \(\| y\|\leq\| x\|\), and \(\| y\|< 1\) implies the existence of \(x\in E\) with \(\| x\|< 1\) and \(-x\leq y\leq x\). This concept is generalized to matrix ordered complex operator spaces [as introduced by \textit{M.-D. Choi} and \textit{E.
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Implicit Regularization in Deep Matrix Factorization
CoRR, 2019 Efforts to understand the generalization mystery in deep learning have led to the belief that gradient-based optimization induces a form of implicit regularization, a bias towards models of low "complexity." We study the implicit regularization of gradient descent over deep linear neural networks for matrix completion and sensing, a model referred to ...
Sanjeev Arora +3 more
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Variation diminution and intervals of sign regular matrices
Results in Applied MathematicsA sign regular matrix is a matrix having the property that its non-zero minors of all orders have, for each order, an identical sign. Such matrices arise in a wide range of applications. In this paper, intervals of real matrices with respect to the usual
Mohammad Adm, Jürgen Garloff
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Some results of neutrosophic normed space VIA Tribonacci convergent sequence spaces
Journal of Inequalities and Applications, 2022 The concept of Tribonacci sequence spaces by the domain of a regular Tribonacci matrix was introduced by Yaying and Hazarika (Math. Slovaca 70(3):697–706, 2000). In this paper, by using the domain of regular Tribonacci matrix T = ( t i k ) $T = (t _{ik} )
Vakeel A. Khan +2 more
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Total Variation Regularization of Matrix‐Valued Images [PDF]
International Journal of Biomedical Imaging, 2007 We generalize the total variation restoration model, introduced by Rudin, Osher, and Fatemi in 1992, to matrix‐valued data, in particular, to diffusion tensor images (DTIs). Our model is a natural extension of the color total variation model proposed by Blomgren and Chan in 1998.
Oddvar Christiansen +4 more
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