Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...

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 ...

Do you remember the early days of social media? The promise of connection, of democratic empowerment, of barriers crumbling and gates opening? In those heady days, the co-founder of Twitter said that ...

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Streaming has undoubtedly changed how we watch movies. While nothing can replace the theatrical experience, the pros of streaming ultimately outweigh the cons. That being said, the prices are getting ...

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 ...

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 difficult tasks in numerical ...

Abstract: The implicitly restarted Arnoldi method (IRAM), which relies on Krylov subspace iteration, is an effective approach for extracting desired partial eigenpairs in characteristic mode analysis ...

YouTube this week put out a new video meant to address creators’ questions over its short-form video platform, YouTube Shorts. The questions it answered ranged from how the algorithm for Shorts ...

Some Python implementations of randomized, matrix-free algorithms for estimating $\text{tr}(A)$, $\text{tr}(A^{-1})$, $\log \det(A)$, $\text{diag}(A)$, $\text{diag}(A ...