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Convert prediction filter polynomial to reflection coefficients


k = poly2rc(a)
[k,r0] = poly2rc(a,efinal)


k = poly2rc(a) converts the prediction filter polynomial a to the reflection coefficients of the corresponding lattice structure. a can be real or complex, and a(1) cannot be 0. If a(1) is not equal to 1, poly2rc normalizes the prediction filter polynomial by a(1). k is a row vector of size length(a)-1.

[k,r0] = poly2rc(a,efinal) returns the zero-lag autocorrelation, r0, based on the final prediction error, efinal.


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Find Reflection Coefficients from Prediction Filter Polynomial

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 =


r0 =



If abs(k(i)) == 1 for any i, finding the reflection coefficients is an ill-conditioned problem. poly2rc returns some NaNs and provides a warning message in those cases.

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A simple, fast way to check if a has all of its roots inside the unit circle is to check if each of the elements of k has magnitude less than 1.

stable = all(abs(poly2rc(a))<1)


poly2rc implements this recursive relationship:

This relationship is based on Levinson's recursion [1]. To implement it, poly2rc loops through a in reverse order after discarding its first element. For each loop iteration i, the function:

  1. Sets k(i) equal to a(i)

  2. Applies the second relationship above to elements 1 through i of the vector a.

    a = (a-k(i)*fliplr(a))/(1-k(i)^2);



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