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For example, in geometry, two linearly independent vectors span a plane. To express that a vector space V is a linear span of a subset S, one commonly uses one of the following phrases: S spans V; S is a spanning set of V; V is spanned or generated by S; S is a generator set or a generating set of V.
In the Cartesian plane, two vectors are said to be perpendicular if the angle between them is 90° (i.e. if they form a right angle). This definition can be formalized in Cartesian space by defining the dot product and specifying that two vectors in the plane are orthogonal if their dot product is zero.
As a further complication, in geometric algebra the inner product and the exterior (Grassmann) product are combined in the geometric product (the Clifford product in a Clifford algebra) – the inner product sends two vectors (1-vectors) to a scalar (a 0-vector), while the exterior product sends two vectors to a bivector (2-vector) – and in ...
The span of G is also the set of all linear combinations of elements of G. If W is the span of G, one says that G spans or generates W, and that G is a spanning set or a generating set of W. [12] Basis and dimension A subset of a vector space is a basis if its elements are linearly independent and span the vector space. [13]
where "old" and "new" refer respectively to the initially defined basis and the other basis, and are the column vectors of the coordinates of the same vector on the two bases. A {\displaystyle A} is the change-of-basis matrix (also called transition matrix ), which is the matrix whose columns are the coordinates of the new basis vectors on the ...
The tensor product of two vector spaces is a vector space that is defined up to an isomorphism.There are several equivalent ways to define it. Most consist of defining explicitly a vector space that is called a tensor product, and, generally, the equivalence proof results almost immediately from the basic properties of the vector spaces that are so defined.
The concept of orthogonality may be extended to a vector space over any field of characteristic not 2 equipped with a quadratic form .Starting from the observation that, when the characteristic of the underlying field is not 2, the associated symmetric bilinear form , = ((+) ()) allows vectors and to be defined as being orthogonal with respect to when (+) () = .
A series Σu k of orthogonal vectors converges in H if and only if the series of squares of norms converges, and ‖ = ‖ = = ‖ ‖. Furthermore, the sum of a series of orthogonal vectors is independent of the order in which it is taken.