Orthogonality
Orthogonal set and basis
An orthogonal set is a set in which all pairs of distinct vectors are orthogonal. Similarly, an orthogonal basis is a basis that is an orthogonal set.
If is an orthogonal basis for a subspace and is a vector in , the scalars that express as a linear combination of are given by:
Orthonormal set and basis
A set of vectors in is called an orthonormal set if it is an orthogonal set of unit vectors. Likewise, an orthonormal basis is an orthonormal set that is a basis for some subspace. You can easily obtain an orthonormal set from an orthogonal set by normalizing each vector in the set.
If is an orthonormal basis for subspace and is in , then can be expressed as a combination of projections:
Orthogonal Matrix
Somewhat confusingly, a square matrix in which the columns form an orthonormal set is called an orthogonal matrix. There is no name for a non-square matrix with orthonormal columns.
An orthogonal matrix some nice properties. Some of these are a bit obvious but it's nice to have them in a list. For any orthogonal matrix with dimension :
.
for any in .
Any eigenvalues of have .
for every and in .
is orthogonal.
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Orthogonal Projection
If is some subspace of and is an orthogonal basis for , for any in , the orthogonal projection of v onto W is defined as:
The component of v orthogonal to W is the vector:
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