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_linearIndependent: if the input vectors ofgramSchmidtare linearly independent, then so are the output vectors.gramSchmidt_ne_zero: if the input vectors ofgramSchmidtare linearly independent, then the output vectors are non-zero.gramSchmidtBasis: the basis produced by the Gram-Schmidt process when given a basis as inputgramSchmidtNormed: the normalizedgramSchmidtprocess, i.e each vector ingramSchmidtNormedhas unit lengthgramSchmidt_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
- InnerProductSpace.gramSchmidt ๐ f n = f n - โ i : { x : ฮน // x โ Finset.Iio n }, (Submodule.span ๐ {InnerProductSpace.gramSchmidt ๐ f โi}).starProjection (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 given an orthogonal set of vectors, gramSchmidt fixes its input.
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
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the normalized gramSchmidt (i.e each vector in gramSchmidtNormed has unit length.)
Equations
- InnerProductSpace.gramSchmidtNormed ๐ f n = (โโInnerProductSpace.gramSchmidt ๐ f nโ)โปยน โข InnerProductSpace.gramSchmidt ๐ f n
Instances For
Gram-Schmidt Orthonormalization:
gramSchmidtNormed applied to a linearly independent set of vectors produces an orthornormal
system of vectors.
Alias of InnerProductSpace.gramSchmidtNormed_orthonormal.
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.
Alias of InnerProductSpace.gramSchmidtNormed_orthonormal'.
Gram-Schmidt Orthonormalization:
gramSchmidtNormed produces an orthornormal system of vectors after removing the vectors which
become zero in the process.
gramSchmidtNormed produces linearly independent vectors when given linearly independent
vectors.
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
Instances For
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.