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Sampling is the practice of reconstructing a function from its values at a finite number of points. The simplest case is to
consider is a function
. Clearly, not every function can be reconstructed, as seen in the example below:
One will note that at the marked points, both the red and the blue functions
are
, but only one is the constant function
, hence sampling would fail at these points.
Hence, some restrictions must be put on
. For a sufficiently nice function
on
, with
,
may be
expanded into a sine series:
.
One says
is band-limited with bandwidth
if
. In this case, one can see that in fact,
Hence, we see that bandlimited functions of bandwidth
, can be reconstructed by sampling from
points.
We wish to study the analogous concept on the Sierpinski Gasket. First, one must note
that
, and hence
is an eigenfunction
of the laplacian of eigenvalue
. Moreover,
, and so
we say that
has Dirichlet boundary conditions. Hence, for a function
defined on the Sierpinski Gasket, we say
is bandlimited if
, where
and
.
It makes the most sense to sample on
, the
th level of the Sierpinski Gasket. One wishes to find functions
such that, for a band limited function
,
.
Hence, we wish to have
, and
for
. Consider the matrix
, letting
and
vary. This matrix is square and invertible due
to a result by Shima and Fukashima. Noting that
, we see that we
ought to define
.
Since this was essentially a change of basis, clearly we will be able to
reconstruct bandlimited functions with these
functions.
Next: Computation of the functions
Up: sampling
Previous: sampling
Brain Street
2001-11-11