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With respect to general linear maps, linear endomorphisms and square matrices have some specific properties that make their study an important part of linear algebra, which is used in many parts of mathematics, including geometric transformations, coordinate changes, quadratic forms, and many other part of mathematics.
He retired on May 15, 2023 after giving his final Linear Algebra and Learning from Data [6] lecture at MIT. [ 7 ] Strang's teaching has focused on linear algebra which has helped the subject become essential for students of many majors.
He is the author of a textbook on Tensor Calculus (2013) as well as an e-workbook on Linear Algebra. He has recorded hundreds of video lectures; several dozen on Tensors (in a video course which may accompany his textbook) as well as over a hundred shorter videos on linear algebra. Many of these are available on YouTube as well as other sites.
Robert A. van de Geijn is a Professor of Computer Sciences at the University of Texas at Austin.He received his B.S. in Mathematics and Computer Science (1981) from the University of Wisconsin–Madison and his Ph.D. in Applied Mathematics (1987) from the University of Maryland, College Park.
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In linear algebra, the Gram matrix (or Gramian matrix, Gramian) of a set of vectors , …, in an inner product space is the Hermitian matrix of inner products, whose entries are given by the inner product = , . [1]
In mathematics, and in particular linear algebra, the Moore–Penrose inverse + of a matrix , often called the pseudoinverse, is the most widely known generalization of the inverse matrix. [1] It was independently described by E. H. Moore in 1920, [2] Arne Bjerhammar in 1951, [3] and Roger Penrose in 1955. [4]