نتایج جستجو برای: g doubly stochastic matrix

تعداد نتایج: 913790  

2008
A. Salemi

Let Mn,m be the set of all n × m matrices with entries in F, where F is the field of real or complex numbers. A matrix R ∈ Mn with the property Re=e, is said to be a g-row stochastic (generalized row stochastic) matrix. Let A,B∈ Mn,m, so B is said to be gw-majorized by A if there exists an n×n g-row stochastic matrix R such that B=RA. In this paper we characterize all linear operators that stro...

1966
Peter D. Lax

In [l] R. Sinkhorn proved the following theorem: Let A be a positive square matrix. Then there exist two diagonal matrices D, , D, whose diagonal elements are positive such that D,AD, is doubly stochastic. Moreover, these matrices are uniquely determkd up to scalar factors. In addition, Sinkhorn gave some examples which show that the theorem fails for some nonnegative matrices A. Marcus and New...

Journal: :international journal of nonlinear analysis and applications 0
zahra sadati department of mathematics, khomein branch, islamic azad university, khomein, iran

this paper presents an approach for solving a nonlinear stochastic differential equations (nsdes) using a new basis functions (nbfs). these functions and their operational matrices areused for representing matrix form of the nbfs. with using this method in combination with the collocation method, the nsdes are reduced a stochastic nonlinear system of equations and unknowns. then, the error anal...

Journal: :Linear Algebra and its Applications 2003

Journal: :Mathematical Models and Methods in Applied Sciences 2020

Journal: :Applied Mathematics Letters 2005

2009
Weiqiang Yang Yufeng Shi

We study reflected solutions of one-dimensional backward doubly stochastic differential equations (BDSDEs in short). The “reflected” keeps the solution above a given stochastic process. We get the uniqueness and existence by penalization. For the existence of backward stochastic integral, our proof is different from [KKPPQ] slightly. We also obtain a comparison theorem for reflected BDSDEs. At ...

Journal: :CoRR 2016
Bin Gu Zhouyuan Huo Heng Huang

Zeroth-order (derivative-free) optimization attracts a lot of attention in machine learning, because explicit gradient calculations may be computationally expensive or infeasible. To handle large scale problems both in volume and dimension, recently asynchronous doubly stochastic zeroth-order algorithms were proposed. The convergence rate of existing asynchronous doubly stochastic zeroth order ...

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