We use the Gram-Schmidt process to calculate an orthogonal basis
Before getting started with the Gram-Schmidt process, here are a few things that we need to recall:
Concept | Example |
---|---|
Vector inner product | Let , |
Vector norm | Let |
Note: An orthogonal set contains non-zero vectors
. Both are orthogonal to each other— for .
Suppose the arbitrary set of linearly independent vectors
We calculate the first vector,
We calculate the second vector,
We calculate the third vector,
We calculate the
The vectors
Find an orthogonal basis for the following vectors that span
The vector
The vector
We get the following equation upon calculation:
The vector
We get the following equation upon calculation:
The following vectors have been calculated using the Gram-Schmidt process that forms the orthogonal basis for
Using the Gram-Schmidt process, an orthonormal basis
Note: An orthonomal set has non-zero vectors
with a norm equal to one— .
To calculate an orthonormal basis, we follow the steps below:
We convert the given set of vectors into an orthogonal basis using the Gram-Schmidt process.
We divide the resulting vectors by their norm to achieve an orthonormal basis.
Let's use the previous example:
The orthogonal set of vectors achieved for
The orthonormal vectors will be calculated in the following way:
To help you completely grasp the Gram-Schmidt process, here are a few questions with solutions:
Find an orthogonal basis for the following vectors that span
Find an orthonormal basis for the following vectors that span
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