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# Linear independence/Related Articles

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*See also changes related to Linear independence, or pages that link to Linear independence or to this page or whose text contains "Linear independence".*

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- Basis (linear algebra) [r]: A set of vectors that, in a linear combination, can represent every vector in a given vector space or free module, and such that no element of the set can be represented as a linear combination of the others.
^{[e]} - Basis (mathematics) [r]:
*Add brief definition or description* - Cauchy-Schwarz inequality [r]: The inequality or its generalization |〈
*x*,*y*〉| ≤ ||*x*|| ||*y*||.^{[e]} - Diagonal matrix [r]: A square matrix which has zero entries off the main diagonal.
^{[e]} - Gram-Schmidt orthogonalization [r]: Sequential procedure or algorithm for constructing a set of mutually orthogonal vectors from a given set of linearly independent vectors.
^{[e]} - Matroid [r]: Structure that captures the essence of a notion of 'independence' that generalizes linear independence in vector spaces.
^{[e]} - Ring (mathematics) [r]: Algebraic structure with two operations, combining an abelian group with a monoid.
^{[e]} - Sequence [r]: An enumerated list in mathematics; the elements of this list are usually referred as to the terms.
^{[e]} - Serge Lang [r]: (19 May 1927 – 12 September 2005) French-born American mathematician known for his work in number theory and for his mathematics textbooks, including the influential
*Algebra*.^{[e]} - Span (mathematics) [r]: The set of all finite linear combinations of a module over a ring or a vector space over a field.
^{[e]} - Vector space [r]: A set of vectors that can be added together or scalar multiplied to form new vectors
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