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  2. Linear independence - Wikipedia

    en.wikipedia.org/wiki/Linear_independence

    The third "5 miles northeast" vector is a linear combination of the other two vectors, and it makes the set of vectors linearly dependent, that is, one of the three vectors is unnecessary to define a specific location on a plane. Also note that if altitude is not ignored, it becomes necessary to add a third vector to the linearly independent set.

  3. Linear subspace - Wikipedia

    en.wikipedia.org/wiki/Linear_subspace

    A basis for a subspace S is a set of linearly independent vectors whose span is S. The number of elements in a basis is always equal to the geometric dimension of the subspace. Any spanning set for a subspace can be changed into a basis by removing redundant vectors (see § Algorithms below for more). Example

  4. Vector space - Wikipedia

    en.wikipedia.org/wiki/Vector_space

    The elements of a subset G of a F-vector space V are said to be linearly independent if no element of G can be written as a linear combination of the other elements of G. Equivalently, they are linearly independent if two linear combinations of elements of G define the same element of V if and only if they have the same coefficients. Also ...

  5. Orthonormality - Wikipedia

    en.wikipedia.org/wiki/Orthonormality

    Consider the restrictions on x 1, x 2, y 1, y 2 required to make u and v form an orthonormal pair. ... Every orthonormal list of vectors is linearly independent.

  6. Basis (linear algebra) - Wikipedia

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

    The elements of a basis are called basis vectors. Equivalently, a set B is a basis if its elements are linearly independent and every element of V is a linear combination of elements of B. [1] In other words, a basis is a linearly independent spanning set.

  7. Dimension theorem for vector spaces - Wikipedia

    en.wikipedia.org/wiki/Dimension_theorem_for...

    By Zorn's lemma, every linearly independent set is contained in a maximal linearly independent set K. This maximality implies that K spans V and is therefore a basis (the maximality implies that every element of V is linearly dependent from the elements of K, and therefore is a linear combination of elements of K).

  8. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    A set of vectors is linearly independent if none is in the span of the others. Equivalently, a set S of vectors is linearly independent if the only way to express the zero vector as a linear combination of elements of S is to take zero for every coefficient a i. A set of vectors that spans a vector space is called a spanning set or generating set.

  9. Gram matrix - Wikipedia

    en.wikipedia.org/wiki/Gram_matrix

    In particular, the vectors are linearly independent if and only if the parallelotope has nonzero n-dimensional volume, if and only if Gram determinant is nonzero, if and only if the Gram matrix is nonsingular. When n > m the determinant and volume are zero.