Results 51 to 60 of about 7,621 (191)
Recurrent Neural Networks for Computing the Moore‐Penrose Inverse with Momentum Learning
We are concerned with a kind of iterative method for computing the Moore-Penrose inverse, which can be considered as a discrete-time form of recurrent neural networks.
Naimin Zhang, Ting Zhang
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This paper presents a computational iterative method to find approximate inverses for the inverse of matrices. Analysis of convergence reveals that the method reaches ninth-order convergence.
F. Soleymani, M. Sharifi, S. Shateyi
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Singular matrices possessing the triangle property
It is known that the inverse of an invertible real square matrix satisfying the triangle property is a tridiagonal matrix. In this note, results that may be considered as analogues of this assertion are obtained for the Moore-Penrose inverse and the ...
Priya K. Kranthi, Sivakumar K. C.
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Some New Algebraic and Topological Properties of the Minkowski Inverse in the Minkowski Space
We introduce some new algebraic and topological properties of the Minkowski inverse A⊕ of an arbitrary matrix A∈Mm,n (including singular and rectangular) in a Minkowski space μ.
Hanifa Zekraoui +2 more
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An improved method for the computation of the Moore-Penrose inverse matrix [PDF]
Vasilios N. Katsikis +2 more
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Using the Kronecker product of matrices, the Moore-Penrose generalized inverse, and the complex representation of quaternion matrices, we derive the expressions of least squares solution with the least norm, least squares pure imaginary solution with the
Shi-Fang Yuan
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Generalized Commutators and the Moore-Penrose Inverse
Irwin S. Pressman
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Spectral permanence for the Moore-Penrose inverse [PDF]
Dragan S. Djordjević +2 more
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New Bounds for the Davis–Wielandt Radius via the Moore–Penrose Inverse of Bounded Linear Operators
In this paper, we obtain some new upper bounds involving powers of the Davis–Wielandt radius of bounded linear operators with closed ranges by using the Moore–Penrose inverse.
Xiaomei Dong, Yuzhen Guo, Deyu Wu
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