Results 21 to 30 of about 4,245 (213)

Existence of Moore-Penrose inverses in rings with involution [PDF]

open access: yesSongklanakarin Journal of Science and Technology (SJST), 2018
We give necessary and sufficient conditions for the existence of the Moore-Penrose inverse of an element in a ring with involution. If R is a ring with involution, we also investigate the existence of the Moore-Penrose inverse of the product 1 2 n x
Wannisa Apairat, Sompong Chuysurichay
doaj   +1 more source

Aggregating distributed energy resources for grid flexibility services: A distributed game theoretic approach

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView., 2023
Abstract We propose a hierarchical energy management scheme for aggregating Distributed Energy Resources (DERs) for grid flexibility services. To prevent a direct participation of numerous prosumers in the wholesale electricity market, aggregators, as self‐interest agents in our scheme, incentivize prosumers to provide flexibility. We firstly model the
Xiupeng Chen   +3 more
wiley   +1 more source

A Parallel Computing Method for the Computation of the Moore–Penrose Generalized Inverse for Shared-Memory Architectures

open access: yesIEEE Access, 2023
The computation of the Moore–Penrose generalized inverse is a commonly used operation in various fields such as the training of neural networks based on random weights.
Elkin Gelvez-Almeida   +3 more
doaj   +1 more source

On the perturbation of the Moore–Penrose inverse of a matrix [PDF]

open access: yesApplied Mathematics and Computation, 2020
The Moore-Penrose inverse of a matrix has been extensively investigated and widely applied in many fields over the past decades. One reason for the interest is that the Moore-Penrose inverse can succinctly express some important geometric constructions in finite-dimensional spaces, such as the orthogonal projection onto a subspace and the linear least ...
openaire   +2 more sources

A Neural Network for Moore–Penrose Inverse of Time-Varying Complex-Valued Matrices

open access: yesInternational Journal of Computational Intelligence Systems, 2020
The Moore–Penrose inverse of a matrix plays a very important role in practical applications. In general, it is not easy to immediately solve the Moore–Penrose inverse of a matrix, especially for solving the Moore–Penrose inverse of a complex-valued ...
Yiyuan Chai   +4 more
doaj   +1 more source

Calculating the Moore–Penrose Generalized Inverse on Massively Parallel Systems

open access: yesAlgorithms, 2022
In this work, we consider the problem of calculating the generalized Moore–Penrose inverse, which is essential in many applications of graph theory.
Vukašin Stanojević   +4 more
doaj   +1 more source

Weighted Moore-Penrose inverse of a boolean matrix [PDF]

open access: yes, 1997
If A is a boolean matrix, then the weighted Moore-Penrose inverse of A (with respect to the given matrices M, N) is a matrix G which satisfies AGA = A, GAG = G, and that MAG and GAN are symmetric.
S.K. Jain   +5 more
core   +3 more sources

Convergence of Rump's method for computing the Moore-Penrose inverse [PDF]

open access: yes, 2016
summary:We extend Rump's verified method (S. Oishi, K. Tanabe, T. Ogita, S. M. Rump (2007)) for computing the inverse of extremely ill-conditioned square matrices to computing the Moore-Penrose inverse of extremely ill-conditioned rectangular matrices ...
Chen, Yunkun, Wei, Yimin, Shi, Xinghua
core   +1 more source

On the mean and variance of the estimated tangency portfolio weights for small samples

open access: yesModern Stochastics: Theory and Applications, 2022
In this paper, a sample estimator of the tangency portfolio (TP) weights is considered. The focus is on the situation where the number of observations is smaller than the number of assets in the portfolio and the returns are i.i.d.
Gustav Alfelt, Stepan Mazur
doaj   +1 more source

Smoothed Analysis of Moore–Penrose Inversion [PDF]

open access: yesSIAM Journal on Matrix Analysis and Applications, 2010
We perform a smoothed analysis of the condition number of rectangular matrices. We prove that, asymptotically, the expected value of this condition number depends only on the elongation of the matrix and not on the center and variance of the underlying probability distribution.
Peter Bürgisser, Felipe Cucker
openaire   +1 more source

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