Convert prediction filter polynomial to reflection coefficients
the prediction filter polynomial
a to the reflection
coefficients of the corresponding lattice structure.
be real or complex, and
a(1) cannot be 0. If
not equal to
1, poly2rc normalizes
the prediction filter polynomial by
a row vector of size
[k,r0] returns the zero-lag
r0, based on the final prediction
Given a prediction filter polynomial,
a, and a final prediction error,
efinal, determine the reflection coefficients of the corresponding lattice structure and the zero-lag autocorrelation.
a = [1.0000 0.6149 0.9899 0.0000 0.0031 -0.0082]; efinal = 0.2; [k,r0] = poly2rc(a,efinal)
k = 0.3090 0.9801 0.0031 0.0081 -0.0082
r0 = 5.6032
abs(k(i)) == 1 for any
finding the reflection coefficients is an ill-conditioned problem.
NaNs and provides a warning message in those
poly2rc implements this recursive relationship:
This relationship is based on Levinson's recursion . To implement it,
a in reverse order after discarding its
first element. For each loop iteration
i, the function:
k(i) equal to
Applies the second relationship above
to elements 1 through
i of the
a = (a-k(i)*fliplr(a))/(1-k(i)^2);
 Kay, Steven M. Modern Spectral Estimation. Englewood Cliffs, NJ: Prentice-Hall, 1988.