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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 combinatorics, a matroid / ˈ m eɪ t r ɔɪ d / is a structure that abstracts and generalizes the notion of linear independence in vector spaces.There are many equivalent ways to define a matroid axiomatically, the most significant being in terms of: independent sets; bases or circuits; rank functions; closure operators; and closed sets or flats.
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.
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]
Baker's Theorem — If , …, are linearly independent over the rational numbers, then for any algebraic numbers , …,, not all zero, we have | + + + | > where H is the maximum of the heights of and C is an effectively computable number depending on n, and the maximum d of the degrees of . (If β 0 is nonzero then the assumption that are linearly independent can be dropped.)
Just as with any linear system of two equations, two solutions may be called linearly-independent if + = implies = =, or equivalently that | ˙ ˙ | is non-zero. This notion is extended to second-order systems, and any two solutions to a second-order ODE are called linearly-independent if they are linearly-independent in this sense.
The concepts of dependence and independence of systems are partially generalized in numerical linear algebra by the condition number, which (roughly) measures how close a system of equations is to being dependent (a condition number of infinity is a dependent system, and a system of orthogonal equations is maximally independent and has a ...