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{{for|bounded sets in general|bounded set}} | |||
In [[functional analysis]] and related areas of [[mathematics]], a [[Set (mathematics)|set]] in a [[topological vector space]] is called '''bounded''' or '''von Neumann bounded''', if every [[neighbourhood (mathematics)|neighborhood]] of the [[zero vector]] can be ''inflated'' to include the set. Conversely a set which is not bounded is called '''unbounded'''. | |||
Bounded sets are a natural way to define a [[locally convex topology|locally convex]] [[polar topology|polar topologies]] on the [[vector space]]s in a [[dual pair]], as the [[polar set|polar]] of a bounded set is an [[absolutely convex]] and [[absorbing set]]. The concept was first introduced by [[John von Neumann]] and [[Andrey Kolmogorov]] in 1935. | |||
== Definition == | |||
Given a [[topological vector space]] (''X'',τ) over a [[field (mathematics)|field]] ''F'', ''S'' is called '''bounded''' if for every neighborhood ''N'' of the zero vector there exists a [[scalar (mathematics)|scalar]] α such that | |||
:<math>S \subseteq \alpha N</math> | |||
with | |||
:<math>\alpha N := \{ \alpha x \mid x \in N\}</math>. | |||
In other words a set is called bounded if it is [[absorbing set|absorbed]] by every [[neighbourhood (mathematics)|neighborhood]] of the zero vector. | |||
In [[locally convex topological vector space]]s the topology τ of the space can be specified by a family ''P'' of [[semi-norm]]s. An equivalent characterization of bounded sets in this case is, a set ''S'' in (''X'',''P'') is bounded if and only if it is bounded for all [[semi normed space]]s (''X'',''p'') with ''p'' a semi norm of ''P''. | |||
== Examples and nonexamples == | |||
* Every finite set of points is bounded | |||
* The set of points of a [[Cauchy sequence]] is bounded, the set of points of a Cauchy [[net (mathematics)|net]] need not to be bounded. | |||
* Every [[relatively compact set]] in a topological vector space is bounded. If the space is equipped with the [[weak topology (polar topology)|weak topology]] the converse is also true. | |||
* A (non null) subspace of a Hausdorff topological vector space is '''not''' bounded | |||
== Properties == | |||
* The [[closure (topology)|closure]] of a bounded set is bounded. | |||
* In a locally convex space, the [[convex envelope]] of a bounded set is bounded. (Without local convexity this is false, as the <math>L^p</math> spaces for <math>0<p<1</math> have no nontrivial open convex subsets.) | |||
* The finite [[union (set theory)|union]] or finite sum of bounded sets is bounded. | |||
* [[Continuous linear mapping]]s between topological vector spaces preserve boundedness. | |||
* A [[locally convex space]] is [[seminormable]] [[if and only if]] there exists a bounded neighbourhood of zero. | |||
* The polar of a bounded set is an absolutely convex and absorbing set. | |||
* A set ''A'' is bounded if and only if every [[countable]] subset of ''A'' is bounded | |||
== Generalization == | |||
The definition of bounded sets can be generalized to [[topological module]]s. A subset ''A'' of a topological module ''M'' over a [[topological ring]] ''R'' is bounded if for any neighborhood ''N'' of ''0<sub>M</sub>'' there exists a neighborhood ''w'' of 0<sub>''R''</sub> such that ''w A ⊂ N''. | |||
== See also == | |||
*[[Totally bounded space]] | |||
*[[Local boundedness]] | |||
*[[bounded function]] | |||
*[[bounding point]] | |||
== References == | |||
* {{cite book |last=Robertson |first=A.P. |coauthors= W.J. Robertson |title= Topological vector spaces |series=Cambridge Tracts in Mathematics |volume=53 |year=1964 |publisher= [[Cambridge University Press]] | pages=44–46 }} | |||
* {{cite book | author=H.H. Schaefer | title=Topological Vector Spaces | publisher=[[Springer-Verlag]] | series=[[Graduate Texts in Mathematics|GTM]] | volume=3 | date=1970 | isbn=0-387-05380-8 | pages=25–26 }} | |||
{{Functional Analysis}} | |||
[[Category:Topological vector spaces]] | |||
[[nl:Begrensdheid]] |
Revision as of 04:48, 14 March 2013
28 year-old Painting Investments Worker Truman from Regina, usually spends time with pastimes for instance interior design, property developers in new launch ec Singapore and writing. Last month just traveled to City of the Renaissance.
In functional analysis and related areas of mathematics, a set in a topological vector space is called bounded or von Neumann bounded, if every neighborhood of the zero vector can be inflated to include the set. Conversely a set which is not bounded is called unbounded.
Bounded sets are a natural way to define a locally convex polar topologies on the vector spaces in a dual pair, as the polar of a bounded set is an absolutely convex and absorbing set. The concept was first introduced by John von Neumann and Andrey Kolmogorov in 1935.
Definition
Given a topological vector space (X,τ) over a field F, S is called bounded if for every neighborhood N of the zero vector there exists a scalar α such that
with
In other words a set is called bounded if it is absorbed by every neighborhood of the zero vector.
In locally convex topological vector spaces the topology τ of the space can be specified by a family P of semi-norms. An equivalent characterization of bounded sets in this case is, a set S in (X,P) is bounded if and only if it is bounded for all semi normed spaces (X,p) with p a semi norm of P.
Examples and nonexamples
- Every finite set of points is bounded
- The set of points of a Cauchy sequence is bounded, the set of points of a Cauchy net need not to be bounded.
- Every relatively compact set in a topological vector space is bounded. If the space is equipped with the weak topology the converse is also true.
- A (non null) subspace of a Hausdorff topological vector space is not bounded
Properties
- The closure of a bounded set is bounded.
- In a locally convex space, the convex envelope of a bounded set is bounded. (Without local convexity this is false, as the spaces for have no nontrivial open convex subsets.)
- The finite union or finite sum of bounded sets is bounded.
- Continuous linear mappings between topological vector spaces preserve boundedness.
- A locally convex space is seminormable if and only if there exists a bounded neighbourhood of zero.
- The polar of a bounded set is an absolutely convex and absorbing set.
- A set A is bounded if and only if every countable subset of A is bounded
Generalization
The definition of bounded sets can be generalized to topological modules. A subset A of a topological module M over a topological ring R is bounded if for any neighborhood N of 0M there exists a neighborhood w of 0R such that w A ⊂ N.
See also
References
- 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 - 20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.
My blog: http://www.primaboinca.com/view_profile.php?userid=5889534