Editing Linear algebra (section)

===Topological vector spaces===
{{main|Topological vector space|Normed vector space|Hilbert space}}
Vector spaces that are not finite-dimensional often require additional structure to be tractable. A [[normed vector space]] is a vector space along with a function called a [[Norm (mathematics)|norm]], which measures the "size" of elements. The norm induces a [[Metric (mathematics)|metric]], which measures the distance between elements, and induces a [[Topological space|topology]], which allows for a definition of continuous maps. The metric also allows for a definition of [[Limit (mathematics)|limits]] and [[Complete metric space|completeness]] &ndash; a normed vector space that is complete is known as a [[Banach space]]. A complete metric space along with the additional structure of an [[Inner product space|inner product]] (a conjugate symmetric [[sesquilinear form]]) is known as a [[Hilbert space]], which is in some sense a particularly well-behaved Banach space. [[Functional analysis]] applies the methods of linear algebra alongside those of [[mathematical analysis]] to study various function spaces; the central objects of study in functional analysis are [[Lp space|{{mvar|L<sup>p</sup>}} space]]s, which are Banach spaces, and especially the {{math|''L''<sup>2</sup>}} space of square-integrable functions, which is the only Hilbert space among them. Functional analysis is of particular importance to quantum mechanics, the theory of partial differential equations, digital signal processing, and electrical engineering. It also provides the foundation and theoretical framework that underlies the Fourier transform and related methods.