# Difference between revisions of "Gram-Schmidt orthogonalization"

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In mathematics, especially in linear algebra, Gram-Schmidt orthogonalization is a sequential procedure or algorithm for constructing a set of mutually orthogonal vectors from a given set of linearly independent vectors. Orthogonalization is important in diverse applications in mathematics and the applied sciences because it can often simplifiy calculations or computations by making it possible, for instance, to do the calculation in a recursive manner.

## The Gram-Schmidt orthogonalization algorithm

Let X be an inner product space over the sub-field  of real or complex numbers with inner product , and let  be a collection of linearly independent elements of X. Recall that linear independence means that



implies that . The Gram-Schmidt orthogonalization procedure constructs, in a sequential manner, a new sequence of vectors  such that:



The vectors  satisfying (1) are said to be orthogonal.

The Gram-Schmidt orthogonalization algorithm is actually quite simple and goes as follows:

Set 
For i = 2 to n,

End

It can easily be checked that the sequence  constructed in such a way will satisfy the requirement (1).