Results 231 to 240 of about 1,179,942 (315)

A new structure-preserving quaternion QR decomposition method for color image blind watermarking

Signal Processing, 2021
Most of the existing color image watermarking schemes are designed to mark each color channel individually, which ignores the correlation of different color channels and the synchronous embedding of watermarks.
Yong Chen, Zhiyuan Jia, Yan Peng, Yaxin Peng, Dan Zhang   +4 more
semanticscholar   +1 more source

Solving Complex-Valued Time-Varying Linear Matrix Equations via QR Decomposition With Applications to Robotic Motion Tracking and on Angle-of-Arrival Localization

IEEE Transactions on Neural Networks and Learning Systems, 2021
The problem of solving linear equations is considered as one of the fundamental problems commonly encountered in science and engineering. In this article, the complex-valued time-varying linear matrix equation (CVTV-LME) problem is investigated. Then, by
V. Katsikis, Spyridon D. Mourtas, P. Stanimirović, Yunong Zhang   +3 more
semanticscholar   +1 more source

A Fast Tensor Completion Method Based on Tensor QR Decomposition and Tensor Nuclear Norm Minimization

IEEE Transactions on Computational Imaging, 2021
Currently, the tensor completion problem has been paid high attention in the machine learning, especially in the field of computer vision and image processing.
Fengsheng Wu, Yaotang Li, Chaoqian Li, Ying Wu   +3 more
semanticscholar   +1 more source

A meshless finite difference method for elliptic interface problems based on pivoted QR decomposition

, 2021
We propose to solve elliptic interface problems by a meshless finite difference method, where the second order elliptic operator and jump conditions are discretized with the help of the QR decomposition of an appropriately rescaled multivariate ...
O. Davydov, Mansour Safarpoor
semanticscholar   +1 more source

QR decomposition on GPUs

Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units, 2009
QR decomposition is a computationally intensive linear algebra operation that factors a matrix A into the product of a unitary matrix Q and upper triangular matrix R. Adaptive systems commonly employ QR decomposition to solve overdetermined least squares problems.
Andrew Kerr, Dan Campbell, Mark A. Richards   +2 more
openaire   +1 more source

System on chip implementation of floating point matrix inversion using modified Gram-Schmidt based QR decomposition on PYNQ FPGA

International Symposium on Smart Electronic Systems, 2021
This work presents a system on chip (SoC) implementation of floating-point matrix inversion using the modified Gram-Schmidt based QR decomposition technique. The SoC realization is carried out using High-Level Synthesis on PYNQZl board.
K. V. S. Kumar, Venkata Reddy Kopparthi, S. Sabat, K. ThulasiramVarma., Rangababu Peesapati   +4 more
semanticscholar   +1 more source

Parallel inverse QR decomposition

Proceedings of the 30th annual Southeast regional conference on - ACM-SE 30, 1992
This paper describes an algorithm and an associated architecture for the parallel implementation of the least squares problem using the inverse QR decomposition. We developed the architecture as a part of our research on the parallel implementation of multidimensional signal processing algorithms.
Hongyu Xu, Winser E. Alexander
openaire   +1 more source

A note on the Gabor-QR decomposition

Proceedings of 1st International Conference on Image Processing, 2002
In this paper, we propose a novel Gabor transformation scheme that is based on the QR decomposition. This Gabor-QR scheme computes the exact Gabor coefficients by solving a system of linear equations Ax=b. The computation is more efficient than iterative schemes and less complicated than other matrix-based methods.
Patrick Lau, Nikolaos Papanikolopoulos, Daniel Boley   +2 more
openaire   +1 more source

A QR Decomposition for Matrix Pencils

BIT Numerical Mathematics, 2000
An efficient and numerically stable modification of the \(QR\) decomposition for solving a linear least squares problem with a matrix of the form \(A+\lambda B\) is given. The idea is to proceed by columns and in step \(i\) the algorithm is driven by data from column \(i\) of the transformed matrices \(B\) and \(A\) in turn.
Spellucci, P., Hartmann, W. M.
openaire   +2 more sources

Row Ordering for a Sparse QR Decomposition

SIAM Journal on Matrix Analysis and Applications, 1994
The QR decomposition \(QAP= {R\brack 0}\) of an \(m\times n\) matrix \(A\) is studied where \(m\geq n\), \(Q\) is an orthogonal matrix composed of orthogonal transformations and determined by Givens rotations, \(P\) is a permutation matrix, and \(R\) is upper triangular. A new row ordering strategy is used to minimize local fill-in.
Thomas H. Robey, Deborah Sulsky
openaire   +1 more source