Highly Nonlinear Approximations for Sparse Signal Representation
Updating the oblique projector
to
We assume that

In order to inductively construct the duals

- i)
-
, i.e.,
- ii)
-
, i.e.
Case i)
Proposition 4
Let
and vectors
in (17) be given. For an arbitrary vector
the dual vectors
computed as
for
and
produce the identical oblique projector as the dual vectors
.




for
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

Case ii)
Proposition 5
Let vector
and vectors
in (17) be given. Thus
the dual vectors
computed as
where
with
,
provide us with the oblique projector
.
The proof these propositions are given in [10].
The codes for updating the dual vectors are
FrInsert.m
and FrInsertBlock.m.



where



Property 2
If vectors
are linearly independent
they are also biorthogonal to the dual
vectors arising inductively from
the recursive equation (19).
The proof of this property is in [10].
