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In linear algebra, a set of elements is termed a vector space when particular requirements are met. For example, let a set consist of vectors u, v, and w. Also let k and l be real numbers, and consider the defined operations of ⊕ and ⊗. The set is a vector space if, under the operation of ⊕, it meets the following requirements:

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The subject of linear algebra involves equations, matrices, and vectors, but you can’t really separate them too much. Even though a particular section focuses on one or the other of the concepts, you find the other topics working their way in and getting included in the discussion.

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The latter include: * A new chapter on singular values and singular vectors, including ways to analyze a matrix of data * A revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages * A new section on linear algebra and cryptography * A new chapter on linear ...

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