a = levinson(r)
a = levinson(r,n)
[a,e] = levinson(r,n)
[a,e,k] = levinson(r,n)
The Levinson-Durbin recursion is an algorithm for finding an all-pole IIR filter with a prescribed deterministic autocorrelation sequence. It has applications in filter design, coding, and spectral estimation. The filter that levinson produces is minimum phase.
a = levinson(r) finds the coefficients of a length(r)-1 order autoregressive linear process which has r as its autocorrelation sequence. r is a real or complex deterministic autocorrelation sequence. If r is a matrix, levinson finds the coefficients for each column of r and returns them in the rows of a. n=length(r)-1 is the default order of the denominator polynomial A(z); that is, a = [1 a(2) ... a(n+1)]. The filter coefficients are ordered in descending powers of z–1.
a = levinson(r,n) returns the coefficients for an autoregressive model of order n.
Note k is computed internally while computing the a coefficients, so returning k simultaneously is more efficient than converting a to k with tf2latc.
levinson solves the symmetric Toeplitz system of linear equations
where r = [r(1) ... r(n+1)] is the input autocorrelation vector, and r(i)* denotes the complex conjugate of r(i). The input r is typically a vector of autocorrelation coefficients where lag 0 is the first element r(1). The algorithm requires O(n2) flops and is thus much more efficient than the MATLAB® \ command for large n. However, the levinson function uses \ for low orders to provide the fastest possible execution.
 Ljung, L., System Identification: Theory for the User, Prentice-Hall, 1987, pp. 278-280.