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Haar Multi-Resolution Analysis (MRA)


Properties
Nesting
Note:
,
— there are functions in
that are not in
.
Density
Separation
Scaling
if and only if
Orthonormal Basis
is an orthonormal basis for
Haar Function Decomposition
Two Bases
,
is orthogonal
can be defined as
(where)
Haar:
We know
. What is
?
Question: How are the
's and
's related?
Theorem.
is the average of its "double" term and the odd that follows it:
Proof. In the arbitary sense, projection in any vector space is given by:
In this case,
Recall the scaling relation:
Plugging this back into our integral gives
quod erat demonstrandum
Example
What's
?





for
or 
Hence
- if
, then 
- if
, then 
- If
, then 
- if
, then 
Then the function
is given by
is just the projection of
onto the space
Wavelet Spaces
and
We saw that ,given
, we can find
We know
is orthogonal to
(it cannot possibly be in
unless
)
What is
?

is an open secret... it stands for "wavelet"
Let
What is a basis for
?
We'll work with
,
,
this means that
, BUT
. Therefore
Now
and
.
This is our wavelet
! (thunderous applause)
We can show that
is an orthonormal basis for
.
, then
where
is the level.