Improved Gradient Neural Networks for Solving Moore–Penrose Inverse of Full-Rank Matrix
Sign Up to like & getrecommendations! 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… read more here.
Keywords: moore penrose; full rank; matrix; penrose inverse ... See more keywords
Rank-Full Arrays for 1-D Mirrored Aperture Synthesis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3070099
Abstract: The antenna array arrangement determines the rank of the transformation matrix in 1-D mirrored aperture synthesis (1-D MAS). Only when the transformation matrix is of full rank can cosine visibilities be precisely solved from the… read more here.
Keywords: rank; transformation matrix; rank transformation; transformation ... See more keywords
Full rank affine invariant submanifolds
Sign Up to like & getrecommendations! Published in 2018 at "Duke Mathematical Journal"
DOI: 10.1215/00127094-2017-0036
Abstract: We show that every GL(2, R) orbit closure of translation surfaces is either a connected component of a stratum, the hyperelliptic locus, or consists entirely of surfaces whose Jacobians have extra endomorphisms. We use this… read more here.
Keywords: affine invariant; rank affine; full rank; invariant submanifolds ... See more keywords