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BUILT-IN MATHEMATICA SYMBOL
Vector Operations
Tutorials »
|
Orthogonalize
Dot
Inner
Normalize
VectorAngle
See Also »
|
Math & Counting Operations on Lists
Matrices and Linear Algebra
Operations on Vectors
New in 6.0: Mathematics & Algorithms
New in 6.0: Matrix & Linear Algebra Functions
More About »
Projection
Projection
finds the projection of the vector
u
onto the vector
v
.
Projection
finds projections with respect to the inner product function
f
.
MORE INFORMATION
For ordinary vectors
u
and
v
, the projection is taken to be
.
»
In
Projection
,
u
and
v
can be any expressions or lists of expressions for which the inner product function
f
applied to pairs yields real results.
»
EXAMPLES
CLOSE ALL
Basic Examples
(2)
Project the vector (5, 6, 7) onto the
x
axis:
Project onto another vector:
Project the vector (5, 6, 7) onto the
x
axis:
In[1]:=
Out[1]=
Project onto another vector:
In[1]:=
Out[1]=
Scope
(4)
Use symbolic vectors:
Assume all variables are real:
Use exact arithmetic to find the projection of
u
onto
v
:
Use machine arithmetic:
Use 20-digit precision arithmetic:
Projection of a complex vector onto another:
Generalizations & Extensions
(1)
Use a different inner product:
Applications
(2)
Find parallel and orthogonal components of a vector:
is the sum of the parallel and orthogonal components:
Unnormalized Gram-Schmidt algorithm (use
Orthogonalize
for a better implementation):
Do Gram-Schmidt on a random set of 3 vectors:
Verify orthogonality:
Generate some orthogonal polynomials:
Properties & Relations
(3)
The projection of
u
onto
v
is in the direction of
v
:
For ordinary vectors
u
and
v
, the projection is taken to be
:
The projection of
u
onto
v
is equivalent to multiplication by an outer product matrix:
SEE ALSO
Orthogonalize
Dot
Inner
Normalize
VectorAngle
TUTORIALS
Vector Operations
MORE ABOUT
Math & Counting Operations on Lists
Matrices and Linear Algebra
Operations on Vectors
New in 6.0: Mathematics & Algorithms
New in 6.0: Matrix & Linear Algebra Functions
New in 6