Gram-Schmidt Orthogonalization and Orthonormalization #
In this file we introduce Gram-Schmidt Orthogonalization and Orthonormalization.
The Gram-Schmidt process takes a set of vectors as input and outputs a set of orthogonal vectors which have the same span.
Main results #
gramSchmidt: the Gram-Schmidt processgramSchmidt_orthogonal:gramSchmidtproduces an orthogonal system of vectors.span_gramSchmidt:gramSchmidtpreserves span of vectors.gramSchmidt_ne_zero: If the input vectors ofgramSchmidtare linearly independent, then the output vectors are non-zero.gramSchmidt_basis: The basis produced by the Gram-Schmidt process when given a basis as input.gramSchmidtNormed: the normalizedgramSchmidt(i.e each vector ingramSchmidtNormedhas unit length.)gramSchmidt_orthonormal:gramSchmidtNormedproduces an orthornormal system of vectors.gramSchmidtOrthonormalBasis: orthonormal basis constructed by the Gram-Schmidt process from an indexed set of vectors of the right size
The Gram-Schmidt process takes a set of vectors as input and outputs a set of orthogonal vectors which have the same span.
Equations
- gramSchmidt ๐ f n = f n - โ i : { x : ฮน // x โ Finset.Iio n }, โ((orthogonalProjection (Submodule.span ๐ {gramSchmidt ๐ f โi})) (f n))
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This lemma uses โ i in instead of โ i :.
Gram-Schmidt Orthogonalisation:
gramSchmidt produces an orthogonal system of vectors.
This is another version of gramSchmidt_orthogonal using Pairwise instead.
gramSchmidt preserves span of vectors.
If the input vectors of gramSchmidt are linearly independent,
then the output vectors are non-zero.
gramSchmidt produces a triangular matrix of vectors when given a basis.
gramSchmidt produces linearly independent vectors when given linearly independent vectors.
When given a basis, gramSchmidt produces a basis.
Equations
- gramSchmidtBasis b = Basis.mk โฏ โฏ
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the normalized gramSchmidt
(i.e each vector in gramSchmidtNormed has unit length.)
Equations
- gramSchmidtNormed ๐ f n = (โโgramSchmidt ๐ f nโ)โปยน โข gramSchmidt ๐ f n
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Gram-Schmidt Orthonormalization:
gramSchmidtNormed applied to a linearly independent set of vectors produces an orthornormal
system of vectors.
Gram-Schmidt Orthonormalization:
gramSchmidtNormed produces an orthornormal system of vectors after removing the vectors which
become zero in the process.
Given an indexed family f : ฮน โ E of vectors in an inner product space E, for which the
size of the index set is the dimension of E, produce an orthonormal basis for E which agrees
with the orthonormal set produced by the Gram-Schmidt orthonormalization process on the elements of
ฮน for which this process gives a nonzero number.
Equations
- gramSchmidtOrthonormalBasis h f = โฏ.choose
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Given an indexed family f : ฮน โ E of vectors in an inner product space E, for which the
size of the index set is the dimension of E, the matrix of coefficients of f with respect to the
orthonormal basis gramSchmidtOrthonormalBasis constructed from f is upper-triangular.