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The linear dependency of a sequence of vectors does not depend of the order of the terms in the sequence. This allows defining linear independence for a finite set of vectors: A finite set of vectors is linearly independent if the sequence obtained by ordering them is linearly independent. In other words, one has the following result that is ...
In mathematics, the Wronskian of n differentiable functions is the determinant formed with the functions and their derivatives up to order n – 1.It was introduced in 1812 by the Polish mathematician Józef Wroński, and is used in the study of differential equations, where it can sometimes show the linear independence of a set of solutions.
In linear algebra, the Gram matrix (or Gramian matrix, Gramian) of a set of vectors , …, in an inner product space is the Hermitian matrix of inner products, whose entries are given by the inner product = , . [1]
Linear combination; Linear span; Linear independence; Scalar multiplication; Basis. Change of basis; Hamel basis; Cyclic decomposition theorem; Dimension theorem for vector spaces. Hamel dimension; Examples of vector spaces; Linear map. Shear mapping or Galilean transformation; Squeeze mapping or Lorentz transformation; Linear subspace. Row and ...
linear form A linear map from a vector space to its field of scalars [8] linear independence Property of being not linearly dependent. [9] linear map A function between vector space s which respects addition and scalar multiplication. linear transformation A linear map whose domain and codomain are equal; it is generally supposed to be invertible.
The alternant can be used to check the linear independence of the functions ,, …, in function space.For example, let () = (), = and choose =, = /.Then the alternant is the matrix [] and the alternant determinant is .
Linear independence — two or more vectors are linearly independent if there is no way to construct one from linear combinations of the others. Matrix exponential — defined by the exponential series. Matrix representation of conic sections; Pseudoinverse — a generalization of the inverse matrix.
The theorem is also known variously as the Hermite–Lindemann theorem and the Hermite–Lindemann–Weierstrass theorem.Charles Hermite first proved the simpler theorem where the α i exponents are required to be rational integers and linear independence is only assured over the rational integers, [4] [5] a result sometimes referred to as Hermite's theorem. [6]