關於本電子書
Linear Algebra offers a unified treatment of both matrix-oriented and theoretical approaches to the course, which will be useful for classes with a mix of mathematics, physics, engineering, and computer science students. Major topics include singular value decomposition, the spectral theorem, linear systems of equations, vector spaces, linear maps, matrices, eigenvalues and eigenvectors, linear independence, bases, coordinates, dimension, matrix factorizations, inner products, norms, and determinants.
關於作者
Elizabeth S. Meckes is Associate Professor at Case Western Reserve University, Ohio. Her research is in probability and analysis, with an emphasis on random matrix theory. She received her bachelor's (2001) and master's (2002) degrees at Case Western Reserve University, and her doctoral degree (2006) at Stanford University. She is currently writing a monograph on random matrices (Cambridge, forthcoming).
Mark W. Meckes is Associate Professor at Case Western Reserve University, Ohio. His research is in analysis and probability, focusing on random matrix theory and metric geometry. He received his bachelor's (1999) and doctoral (2003) degrees at Case Western Reserve University, Ohio.
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