In applied mathematics, the transfer matrix is a formulation in terms of a block-Toeplitz matrix of the two-scale equation, which characterizes refinable functions.
Refinable functions play an important role in wavelet theory and finite element theory.
, which is a vector with component indexes from
, the transfer matrix of
, we call it
here, is defined as More verbosely The effect of
can be expressed in terms of the downsampling operator "
": More precisely: Let
be the even-indexed coefficients of
be the odd-indexed coefficients of
det
{\displaystyle \det T_{h}=(-1)^{\lfloor {\frac {b-a+1}{4}}\rfloor }\cdot h_{a}\cdot h_{b}\cdot \mathrm {res} (h_{\mathrm {e} },h_{\mathrm {o} })}
{\displaystyle \mathrm {res} }
is the resultant.
det
= det
⋅ det
{\displaystyle \det T_{g*h}=\det T_{g}\cdot \det T_{h}\cdot \mathrm {res} (g_{-},h)}
⋅ x = λ ⋅ x
is an eigenvector of
with respect to the same eigenvalue, i.e. Let
be the periodization of
with respect to period
is a circular filter, which means that the component indexes are residue classes with respect to the modulus
Then with the upsampling operator
it holds
{\displaystyle \mathrm {tr} (T_{h}^{n})=\left(C_{k}h*(C_{k}h\uparrow 2)*(C_{k}h\uparrow 2^{2})*\cdots *(C_{k}h\uparrow 2^{n-1})\right)_{[0]_{2^{n}-1}}}
ϱ (
is the size of the filter and if all eigenvalues are real, it is also true that
ϱ (