Ví dụ về việc sử dụng A vector space trong Tiếng anh và bản dịch của chúng sang Tiếng việt
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What isn't a vector space?
Is a vector space over R{\displaystyle\mathbb{R}}.
Basis and dimension of a vector space.
Note, that a vector space can have several bases.
The position is represented as a point in a vector space.
If the object is a vector space we have a linear representation.
Similar words are closer to each other in a vector space.
Unlike for a vector space, a module doesn't always have a basis.
Given a field extension L/K,the larger field L can be considered as a vector space over K.
Two elements u and v of a vector space with bilinear form B are orthogonal when Bu.
In the case of permutation groups, X is a set; for matrix groups,X is a vector space.
Most often, the set is a vector space, and the group represents symmetries of the vector space. .
Kismet has an underlying, three-dimensional emotional space, a vector space, of where it is emotionally.
The most simple example of a vector space over a field F is the field itself, equipped with its standard addition and multiplication.
The Grassmannian G(k, V) of a vector space V over a field F is the modulispace of all k-dimensional linear subspaces of V.
In mathematics, the linear span(also called the linear hull or just span)of a set S of vectors(from a vector space), denoted span(S),[1] is the smallest linear subspace that contains the set.
In contrast to a basis of a vector space, a basis of topological space need not be maximal; indeed, the only maximal base is the topology itself.
In mathematics, an algebraic number field(or simply number field) F is a finite degree(and hence algebraic) field extension of the field of rational numbers Q. Thus F is a field that contains Q andhas finite dimension when considered as a vector space over Q.
Formally, these are the axioms for a module, so a vector space may be concisely described as a module over a field.
By the very definition of a vector space, one can form the product of any scalar with any vector, giving a map R× V→ V{\displaystyle\mathbb{R}\times V\rightarrow V}.
If one chooses a base point(as zero),then an affine space becomes a vector space, which one may then projectivize, but this requires a choice.
Let K be a field, and let A be a vector space over K equipped with an additional binary operation from A× A to A, denoted here by·(i.e. if x and y are any two elements of A, x· y is the product of x and y).
Theorem 1: The subspace spanned by a non-empty subset S of a vector space V is the set of all linear combinations of vectors in S.
In linear algebra, a basis of a vector space V is a linearly independent subset B such that every element of V is a linear combination of B. Because of the empty sum convention, the zero-dimensional vector space V={0} has a basis, namely the empty set.
The space of all(suitable)real-valued functions on the real numbers is a vector space, and the differential operator d d x{\displaystyle{\frac{d}{dx}}} is a linear operator.
In mathematics, the dimension of a vector space V is the cardinality(i.e. the number of vectors) of a basis of V over its base field.[1][2] It is sometimes called Hamel dimension(after Georg Hamel) or algebraic dimension to distinguish it from other types of dimension.
For every vector space there exists a basis,[lower-alpha 1]and all bases of a vector space have equal cardinality;[lower-alpha 2] asa result, the dimension of a vector space is uniquely defined.
In linear algebra, the quotient of a vector space V by a subspace N is a vector space obtained by"collapsing" N to zero.
Given a field extension L/ K,the larger field L can be considered as a vector space over K. The elements of L are the"vectors" and the elements of K are the"scalars", with vector addition and scalar multiplication obtained from the corresponding field operations.