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In mathematics, more specifically in functional analysis, a Banach space (pronounced ) is a complete normed vector space.Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vectors and is complete in the sense that a Cauchy sequence of vectors always converges to a well-defined limit that is within the space.
As the standard negator is used in the above definition of a t-norm/t-conorm pair, this can be generalized as follows: A De Morgan triplet is a triple (T,⊥,n) such that [1] T is a t-norm; ⊥ is a t-conorm according to the axiomatic definition of t-conorms as mentioned above; n is a strong negator
In functional analysis, an F-space is a vector space over the real or complex numbers together with a metric: such that Scalar multiplication in X {\displaystyle X} is continuous with respect to d {\displaystyle d} and the standard metric on R {\displaystyle \mathbb {R} } or C . {\displaystyle \mathbb {C} .}
Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of vector spaces endowed with some kind of limit-related structure (for example, inner product, norm, or topology) and the linear functions defined on these spaces and suitably respecting these structures.
Inner product spaces are a subset of normed vector spaces, which are a subset of metric spaces, which in turn are a subset of topological spaces. In mathematics, a normed vector space or normed space is a vector space over the real or complex numbers on which a norm is defined. [1]
Banach lattices are extremely common in functional analysis, and "every known example [in 1948] of a Banach space [was] also a vector lattice." [1] In particular: ℝ, together with its absolute value as a norm, is a Banach lattice.
Uniform Boundedness Principle — Let be a Banach space, a normed vector space and (,) the space of all continuous linear operators from into . Suppose that F {\displaystyle F} is a collection of continuous linear operators from X {\displaystyle X} to Y . {\displaystyle Y.}
The space of distributions, being defined as the continuous dual space of (), is then endowed with the (non-metrizable) strong dual topology induced by () and the canonical LF-topology (this topology is a generalization of the usual operator norm induced topology that is placed on the continuous dual spaces of normed spaces).