Abstract: The sparse array could reduce the cost of physical antennas. However, implementing wideband beamforming directly based on the covariance matrix of the received signals from the sparse array ...
This document is designed to help users quickly understand, use, and maintain the Python implementation of the Matrix-Sparsity-Based Pauli Decomposition (MSPD) algorithm. It specifies the function, ...
School of Power and Energy, Nanchang Hangkong University, Nanchang, China. China’s aviation industry, particularly its civil aviation sector, is undergoing rapid development, with the fleet of civil ...
Abstract: Factorizing a low-rank matrix into two matrix factors with low dimensions from its noisy observations is a classical but challenging problem arising from real-world applications. This paper ...
Gregg is professor of neurobiology and human genetics at the University of Utah. In 2018, I waited until after Christmas to inform my 10- and 12-year-old children that I had metastatic male breast ...
Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...
Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...
ABSTRACT: Node renumbering is an important step in the solution of sparse systems of equations. It aims to reduce the bandwidth and profile of the matrix. This allows for the speeding up of the ...
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