MATLAB SIGNAL PROCESSING BLOCKSET 7 Betriebsanweisung Seite 423

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Levinson-Durbin
5-266
average (MA) process (or FIR filter) that predicts the next value of a signal
from the current signal sample and a finite number of past samples. In this
case, the input to the block represents the signal’s autocorrelation sequence,
with
r(1) being the zero-lag value, and the output at the block’s A port contains
the coefficients of the predictive MA process (in descending powers of z).
These coefficients solve the optimization problem below.
Again, the output at the block’s
K port contains the corresponding reflection
coefficients,
[k(1) k(2) ... k(n)], for the lattice realization of this FIR
filter. The Autocorrelation LPC block in the Linear Prediction library
implements this autocorrelation-based prediction method.
Algorithm The algorithm requires O(n
2
) operations, and is thus much more efficient for
large n than standard Gaussian elimination, which requires O(n
3
) operations.
Dialog Box
Output(s)
The solution representation of Ra = b to output: model coefficients (
A),
reflection coefficients (
K), or both (AandK). For scalar inputs, this
parameter must be set to
A.
Hz() Az() 1 a 2()z
1
an 1+()z
n
+++==
min
a
i
{}
Ex
n
a
i
x
ni
i 1=
N
2
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