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| == Coordinatization == Given a space (like ''R^n^'') and bases that span that space (the set ''B = u,,1,, ... u,,n,,''), any vector ''v'' in that space can be represented as a linear combination of the bases. In other words, there must be a set of coefficients ''c,,1,, ... c,,n,,'' that satisfy: ''c,,1,,u,,1,, + ... + c,,n,,u,,n,, = v'' The vector of coefficients (''v,,B,, = [c,,1,,, ... c,,n,,]'') is called the '''coordinate vector''' relative to ''B''. By rewriting the set of bases as a matrix '''''M''',,B,,'', the above statement becomes: '''''M''',,B,, v,,B,, = v'' ''v,,B,,'' can then be identified through [[LinearAlgebra/Elimination|elimination]] of the augmented matrix ''[u,,1,, ... u,,n,, | v]'', or through most software packages as '''''M''',,B,, \ v''. ---- |
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Following from the above notation, a change of basis matrix '''''C''''' that transforms from ''B'' to ''B'``'' satisfies: ''v,,B',, = '''C''' v,,B,,'' |
Basis
The bases for a linear space describe the space. Each member basis is independent.
Contents
Description
Bases are independent vectors that can be linearly combined to reach every other vector in a linear space. If a basis vector is removed, the space necessarily shrinks.
If the basis vectors are orthonormalized, they form an orthonormal basis. A convenient pair of orthonormal basis vectors in R2 are [1 0] and [0 1]. A convenient set of orthonormal basis vectors in R3 are [1 0 0], [0 1 0], and [0 0 1]. And so on.
A null space has no basis.
All non-null spaces have infinitely many possible bases to choose from, because the only requirement on a basis is that it be independent.
Coordinatization
Given a space (like Rn) and bases that span that space (the set B = u1 ... un), any vector v in that space can be represented as a linear combination of the bases. In other words, there must be a set of coefficients c1 ... cn that satisfy:
c1u1 + ... + cnun = v
The vector of coefficients (vB = [c1, ... cn]) is called the coordinate vector relative to B.
By rewriting the set of bases as a matrix MB, the above statement becomes:
MB vB = v
vB can then be identified through elimination of the augmented matrix [u1 ... un | v], or through most software packages as MB \ v.
Change of Basis
A space can be linearly transformed to bring about a change of basis. This transformation can be expressed with a matrix. The inverse of that matrix then also expresses the inverse of the change of basis.
Following from the above notation, a change of basis matrix C that transforms from B to B' satisfies:
vB' = C vB
Such a change of basis has a linear scaling effect on space. The scaling factor is the determinant. If the determinant is 0, then the matrix expresses a transformation that removes one (or more) basis vector(s). Such a transformation effectively collapses the space to a lower dimension.
Any matrix that has basis is invertible, and therefore has a non-zero determinant.
Usage
If a matrix is diagonalizable, identifying the change of basis that transforms it into a diagonal matrix enables several efficient strategies for solving systems.