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First of all, construct a central approximation space
,
which is a subspace of the space of square-integrable functions
, which (a) is spanned by a translation-generated
(a.k.a. ``Riesz'') basis
and (b) is orthonormal:
 |
(278) |
The existence of such a basis is equivalent to the statement that
is closed under integral shifts of its elements, i.e.
The function
, known as a scaling
function (a.k.a. ``father wavelet'') can be
any square integrable function as long as it satisfies the
integer-shifted orthonormality condition, Eq.(2.78).
A particular example of such a basis is the set of wave packets
, Eq.(2.64) on
page
:
For this basis the scaling function is obtained by setting
and letting
:
 |
(280) |
This scaling function happens to be one whose Fourier transform has
compact support and is piecewise constant:
The central approximation space
is spanned by the
orthonormal basis
 |
(281) |
It is the vector space of ``band-limited'' functions, i.e. functions
whose Fourier transforms have compact support on the frequency
interval
. The basis for this space is generated by
Eq.(2.80) and it is called the
Shannon basis.
Figure 2.20:
Partitioning of phase space by a collection hierarchical sets of band limited orthonormal
basis functions. The heavy-lined rectangles are the phase space cells
of low resolution wave packets; they span the
st resolution
vector space
. The shaded rectangles are those of the
next (i.e. more refined) resolution wave packets; they span the
th resolution vector space
. The thin and tall
unshaded rectangles are those of the wave packets of still higher
resolution. They span the
st resolution vector space
. The unshaded rectangle in the middle is the phase space cell
of the ``father wavelet'', the scaling function in
Eq.(2.80). It yields (by compression
and translation) all basis functions for all the vector spaces
.
 |
Next: Translation Followed by Compression
Up: Multiresolution Analysis as Hierarchical
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Ulrich Gerlach
2007-04-05