Vector projection
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The vector resolute (also known as the vector projection) of two vectors,
in the direction of
(also "
on
"), is given by:
where θ is the angle between the vectors
and
; the operator
is the dot product; and
is the unit vector in the direction of
.
The vector resolute is a vector, and is the orthogonal projection of the vector
onto the vector
. The vector resolute is also said to be a component of vector
in the direction of vector
.
The other component of
(perpendicular to
) is given by:
The vector resolute is also the scalar resolute multiplied by
(in order to convert it into a vector, or give it direction).
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[edit] Vector resolute overview
If A and B are two vectors, the projection (C) of A on B is the vector that has the same slope as B with the length:
To calculate C use the definition of the dot product: 
Using the above equation:
Multiply and divide by | B | at the same time:
In the resulting fraction, the top term is the same as the dot product, hence:
To find the length of | C | with an unknown θ, and unknown direction, multiply it with the unit vector B:
giving the final formula:
[edit] Matrix representation
The orthogonal projection can be represented by a projection matrix. To project a vector onto the unit vector a = (ax, ay, az), it would need to be multiplied with this projection matrix:
[edit] Uses
The vector projection is an important operation in the Gram-Schmidt orthonormalization of vector space bases.
[edit] See also
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