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  2. Basis (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Basis_(linear_algebra)

    The same vector can be represented in two different bases (purple and red arrows). In mathematics, a set B of vectors in a vector space V is called a basis (pl.: bases) if every element of V may be written in a unique way as a finite linear combination of elements of B.

  3. Vector space - Wikipedia

    en.wikipedia.org/wiki/Vector_space

    A subset of a vector space is a basis if its elements are linearly independent and span the vector space. [13] Every vector space has at least one basis, or many in general (see Basis (linear algebra) § Proof that every vector space has a basis). [14]

  4. Change of basis - Wikipedia

    en.wikipedia.org/wiki/Change_of_basis

    Consider a linear map T: W → V from a vector space W of dimension n to a vector space V of dimension m. It is represented on "old" bases of V and W by a m × n matrix M . A change of bases is defined by an m × m change-of-basis matrix P for V , and an n × n change-of-basis matrix Q for W .

  5. Standard basis - Wikipedia

    en.wikipedia.org/wiki/Standard_basis

    Every vector a in three dimensions is a linear combination of the standard basis vectors i, j and k.. In mathematics, the standard basis (also called natural basis or canonical basis) of a coordinate vector space (such as or ) is the set of vectors, each of whose components are all zero, except one that equals 1. [1]

  6. Dual basis - Wikipedia

    en.wikipedia.org/wiki/Dual_basis

    The association of a dual basis with a basis gives a map from the space of bases of V to the space of bases of V ∗, and this is also an isomorphism. For topological fields such as the real numbers, the space of duals is a topological space , and this gives a homeomorphism between the Stiefel manifolds of bases of these spaces.

  7. Examples of vector spaces - Wikipedia

    en.wikipedia.org/wiki/Examples_of_vector_spaces

    Both vector addition and scalar multiplication are trivial. A basis for this vector space is the empty set, so that {0} is the 0-dimensional vector space over F. Every vector space over F contains a subspace isomorphic to this one. The zero vector space is conceptually different from the null space of a linear operator L, which is the kernel of L.

  8. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The row space of this matrix is the vector space spanned by the row vectors. The column vectors of a matrix. The column space of this matrix is the vector space spanned by the column vectors. In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column ...

  9. Basis function - Wikipedia

    en.wikipedia.org/wiki/Basis_function

    In mathematics, a basis function is an element of a particular basis for a function space.Every function in the function space can be represented as a linear combination of basis functions, just as every vector in a vector space can be represented as a linear combination of basis vectors.