Examples of using Vector spaces in English and their translations into Romanian
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Metrics on vector spaces.
Vector spaces with additional structure.
Scalars of vector spaces.
Any two vector spaces over F having the same dimension are isomorphic.
Tensor products of vector spaces.
General vector spaces do not possess a multiplication between vectors. .
Therefore, the set of such functions are vector spaces.
Subspaces of V are vector spaces(over the same field) in their own right.
In a similar vein,the solutions of homogeneous linear differential equations form vector spaces.
In such topological vector spaces one can consider series of vectors. .
Banach spaces, introduced by Stefan Banach, are complete normed vector spaces.
Therefore, two vector spaces are isomorphic if their dimensions agree and vice versa.
Those modules that do(including all vector spaces) are known as free modules.
A type(p, q) tensor is defined in this context as an element of the tensor product of vector spaces,[7][8].
The relation of two vector spaces can be expressed by linear map or linear transformation.
This table shows important examples of tensors on vector spaces and tensor fields on manifolds.
Vector spaces have manifold applications as they occur in many circumstances, namely wherever functions with values in some field are involved.
Peano was the first to give the modern definition of vector spaces and linear maps in 1888.[10].
Furthermore, vector spaces furnish an abstract, coordinate-free way of dealing with geometrical and physical objects such as tensors.
Other examples of infinite dimensional normed vector spaces can be found in the Banach space article.
The vector spaces of a tensor product need not be the same, and sometimes the elements of such a more general tensor product are called"tensors".
Most notably, in functional analysis pseudometrics often come from seminorms on vector spaces, and so it is natural to call them"semimetrics".
Infinite-dimensional vector spaces arise naturally in mathematical analysis, as function spaces, whose vectors are functions.
The minimax theorem of game theory stating the existence of a unique payoff when all players play optimally can be formulated andproven using vector spaces methods.
A vector bundle is a family of vector spaces parametrized continuously by a topological space X.
Vector spaces, including infinite-dimensional ones, then became a firmly established notion, and many mathematical branches started making use of this concept.
In fact, Grassmann's 1844 work exceeds the framework of vector spaces, since his consideration of multiplication led him to what are today called algebras.
However, vector spaces per se do not offer a framework to deal with the question- crucial to analysis- whether a sequence of functions converges to another function.
In the infinite-dimensional case, however, there will generally be inequivalent topologies,which makes the study of topological vector spaces richer than that of vector spaces without additional data.
They are then essentially identical as vector spaces, since all identities holding in V are, via f, transported to similar ones in W, and vice versa via g.