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Published in 2020 at "Advances in Applied Clifford Algebras"
DOI: 10.1007/s00006-020-01058-8
Abstract: Using the concept of a transposition anti-involution in Clifford algebra $$C \, \ell _{1,1}$$ C ℓ 1 , 1 and the isomorphisms $${\mathbb {H}}_s \cong C \, \ell _{1,1} \cong \text {Mat}(2,{\mathbb {R}}),$$ H s…
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Keywords:
moore penrose;
split quaternions;
penrose inverse;
singular value ... See more keywords
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Published in 2019 at "Neural Processing Letters"
DOI: 10.1007/s11063-019-09983-x
Abstract: Being with parallel-computation nature and convenience of hardware implementation, linear gradient neural networks (LGNN) are widely used to solve large-scale online matrix-involved problems. In this paper, two improved GNN (IGNN) models, which are activated by…
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Keywords:
moore penrose;
full rank;
matrix;
penrose inverse ... See more keywords
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Published in 2017 at "Linear Algebra and its Applications"
DOI: 10.1016/j.laa.2017.05.026
Abstract: Abstract For a matrix A, let A † denote its Moore–Penrose inverse. A matrix M is called a multiplicative perturbation of T ∈ C m × n if M = E T F ⁎ for…
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Keywords:
moore penrose;
generalized triple;
penrose inverse;
reverse order ... See more keywords
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Published in 2018 at "International Journal of Computer Mathematics"
DOI: 10.1080/00207160.2017.1294689
Abstract: It is well known that the upper bounds of the weighted Moore–Penrose inverse play a fundamental role in the perturbation analysis for the weighted linear least squares problem. In this note, we provide a sharp…
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Keywords:
moore penrose;
acute perturbation;
bounds weighted;
weighted moore ... See more keywords
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Published in 2020 at "IEEE Microwave Magazine"
DOI: 10.1109/mmm.2020.3023220
Abstract: Digital predistortion (DPD) is the linearization technique most often used to cope with the inherent tradeoff between linearity and efficiency in power amplifiers (PAs). Adaptation is needed to optimize DPD performance. This article reviews strategies…
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Keywords:
linearization;
predistortion;
moore penrose;
penrose inverse ... See more keywords
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2
Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2021.3064241
Abstract: Training neural networks with the Moore–Penrose (MP) inverse has recently gained attention in view of its noniterative training nature. However, a significant drawback of learning based on the MP inverse is that the computational memory…
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Keywords:
moore penrose;
inverse;
network learning;
blockwise recursive ... See more keywords
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Published in 2023 at "Filomat"
DOI: 10.2298/fil2301173s
Abstract: Motivated by the representation for the Moore-Penrose inverse of the block matrix over a *-regular ring presented in [R.E. Hartwig and P. Patr?cio, When does the Moore-Penrose inverse flip? Operators and Matrices, 6(1):181-192, 2012], we…
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Keywords:
note moore;
moore penrose;
block matrices;
penrose inverse ... See more keywords