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We denote by
the difference between the function space
spanned
by scaling functions
and the function
spanned by
, i.e.
(where
represents the union of the two spaces).
is composed of all
functions representable in
but not representable in
(as the scale
of the basis functions of
is too coarse for the details of these functions).
This can be carried out recursively to get:
and finally:
Similar to a function space
spanned by the scaling functions
, the function space
is also spanned by a set of basis
function, called the wavelet functions:
We see that the scaling sequence and the wavelet sequence correspond to
low-pass filter and band-pass filter, respectively.
Also, as the wavelet functions
are members of the space
they span as well as all the super-spaces:
they can be expanded in the space
of next higher scale with doubled
resolution:
where
are the expansion coefficients. Usually we let
and drop
the subscripts
and
to indicate that any wavelet function
can be
expressed as a linear combination of the basis scaling functions
of the space with the next higher resolution:
This is in the same form for the scaling functions:
It can be shown that the coefficients of the two expressions are related
Examples:
The Haar scaling function
is a square pulse with unit height and
width, and the coefficients are
. Now
the coefficients for the wavelet functions can be obtained as
and the wavelet function is:
where the two coefficients
are the second
row of the Haar matrix
.
The first two panels show the wavelet functions of scale
:
and
. Note
can be generated by the linear combination of
and
:
The 3rd panel shows the wavelet functions of scale
:
. The 4th panel shows a function in space
spanned by
.
The 5th panel shows a function in space
spanned by
.
The 6th panel shows a function in space
, a linear
combination of
, or
and
.
Next: Wavelet Expansion
Up: wavelets
Previous: Scaling Functions
Ruye Wang
2008-12-16