Examples
a = [1.0000 0.4288 0.76 0.0404 -0.02]; efinal = 0.2; // Step prediction error r = poly2ac(a,efinal) // Autocorrelation sequence |  |  |
Convert prediction polynomial to autocorrelation sequence.
R = poly2ac(a,efinal)
input prediction polynomial with 1st element 1 (if not, poly2ac normalizes it to 1 before proceeding).
input prediction error
output autocorrelation sequence
This function obtains the underlying autocorrelation sequence that would best fit a linear prediction filter described by the denominator polynomial and the numerator scaling. The filter is H(z) = efinal/(a(1) + a(2) x z a(3) x z^2 ... a(n) x z^n-1)
a = [1.0000 0.4288 0.76 0.0404 -0.02]; efinal = 0.2; // Step prediction error r = poly2ac(a,efinal) // Autocorrelation sequence | | |
S. Kay, Modern Spectral Estimation, Prentice Hall, N.J., 1987, Chapter 6.