Linear algebra is the foundation of science and engineering. Knowledge of linear algebra is a prerequisite for studying statistics, machine learning, computer graphics, signal processing, chemistry, ...

This short course is a quick review of linear algebra, intended for students who have already taken a previous course in linear algebra or have some experience with vectors and matrices. The goal of ...

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Abstract: The identification of signal subspace is a crucial operation in hyperspectral imagery, enabling a correct dimensionality reduction that often yields gains ...

Abstract: In this paper, we address the subspace clustering problem. Given a set of data samples (vectors) approximately drawn from a union of multiple subspaces, our goal is to cluster the samples ...

TbGAL is a C++/Python library for Euclidean, homogeneous/projective, Mikowski/spacetime, conformal, and arbitrary geometric algebras with assuming (p, q) metric ...

Casey Murphy has fanned his passion for finance through years of writing about active trading, technical analysis, market commentary, exchange-traded funds (ETFs), commodities, futures, options, and ...

Daniel Liberto is a journalist with over 10 years of experience working with publications such as the Financial Times, The Independent, and Investors Chronicle. Amy is an ACA and the CEO and founder ...

Using the exact results for integrals of exponentials of polynomials of Grassmann variables and the Feynman construction of path integrals, an approximate method is presented to calculate the ...