Abstract: Sparse arrays offer economic advantages by reducing the number of antennas. However, directly utilizing the covariance matrix of sparse array signals for wideband beamforming may lead to the ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Motivation: Sparse matrices containing mostly zeros are commonplace in many applications of data science and machine learning (e.g., adjacency matrices of graphs, one-hot-encoded data, sparsified ...

If folks have libraries who are using SciPy sparse matrices, and you'd like help converting them to run/work with sparse array, this sounds like a nice opportunity to work that out. I wrote a ...

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 ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

A new technical paper titled “Signal processing architecture for a trustworthy 77GHz MIMO Radar” was published by researchers at Fraunhofer FHR, Ruhr University Bochum, and Wavesense Dresden GmbH.

Hefei National Laboratory for Physical Sciences at the Microscale, Department of Chemical Physics, and Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science ...