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Near-Field Source Localization in Nonuniform Noise: An Efficient Symmetric Matrix Factorization-Based Approach. [PDF]

Sensors (Basel)
Song W, He Z, Sun G, Feng S.
europepmc   +1 more source

Taurine Supplementation in Low-Fishmeal of Golden Pompano (<i>Trachinotus ovatus</i>) Diets: Improving Intestinal Health and Alleviation of Inflammatory Response. [PDF]

Animals (Basel)
Wang Z, Ye H, Huang Z, Wang J, Wang Y, Yu W, Lin H, Ma Z, Zhou C.   +8 more
europepmc   +1 more source

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Coded QR Decomposition

2020 IEEE International Symposium on Information Theory (ISIT), 2020
QR decomposition of a matrix is one of the essential operations that is used for solving linear equations and finding least-squares solutions. We propose a coded computing strategy for parallel QR decomposition with applications to solving a full-rank ...
Q. M. Nguyen, Haewon Jeong, P. Grover
semanticscholar   +2 more sources

Real-domain QR decomposition models employing zeroing neural network and time-discretization formulas for time-varying matrices

Neurocomputing, 2021
This study investigated the problem of QR decomposition for time-varying matrices. We transform the original QR decomposition problem into an equation system using its constraints.
Zhenyu Li, Yunong Zhang, Liangjie Ming, Jinjin Guo, V. Katsikis   +4 more
semanticscholar   +2 more sources

QR Decomposition of Dual Matrices and its Application to Traveling Wave Identification in the Brain

Applied Mathematics Letters
Matrix decompositions in dual number representations have played an important role in fields such as kinematics and computer graphics in recent years. In this paper, we present a QR decomposition algorithm for dual number matrices, specifically geared ...
Renjie Xu, Tong Wei, Yimin Wei, Pengpeng Xie   +3 more
semanticscholar   +3 more sources

IDR/QR: an incremental dimension reduction algorithm via QR decomposition

IEEE Transactions on Knowledge and Data Engineering, 2004
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the literature, a well-known dimension reduction algorithm is linear discriminant analysis (LDA).
Jieping Ye, Qi Li 0001, Hui Xiong 0001, Haesun Park, Ravi Janardan, Vipin Kumar 0001   +5 more
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High-Performance QR Decomposition for FPGAs

Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018
QR decomposition (QRD) is of increasing importance for many current applications, such as wireless and radar. Data dependencies in known algorithms and approaches, combined with the data access patterns used in many of these methods, restrict the achievable performance in software programmable targets.
M. Langhammer, B. Pasca
semanticscholar   +2 more sources

Quantum QR decomposition in the computational basis

Quantum Information Processing, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guangsheng Ma, Hongbo Li, Jiman Zhao
semanticscholar   +3 more sources

On the QR decomposition of $${\fancyscript {H}}$$ -matrices [PDF]

Computing, 2010
The hierarchical ($${\fancyscript{H}}$$-) matrix format allows storing a variety of dense matrices from certain applications in a special data-sparse way with linear-polylogarithmic complexity. Many operations from linear algebra like matrix–matrix and matrix–vector products, matrix inversion and LU decomposition can be implemented efficiently using ...
Peter Benner, Thomas Mach
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