Compute reflection coefficients from autocorrelation sequence

`k = schurrc(r)`

[k,e] = schurrc(r)

`k = schurrc(r)`

uses
the Schur algorithm to compute a vector `k`

of reflection
coefficients from a vector `r`

representing an autocorrelation
sequence. `k`

and `r`

are the same
size. The reflection coefficients represent the lattice parameters
of a prediction filter for a signal with the given autocorrelation
sequence, `r`

. When `r`

is a matrix, `schurrc`

treats
each column of `r`

as an independent autocorrelation
sequence, and produces a matrix `k`

, the same size
as `r`

. Each column of `k`

represents
the reflection coefficients for the lattice filter for predicting
the process with the corresponding autocorrelation sequence `r`

.

`[k,e] = schurrc(r)`

also
computes the scalar `e`

, the prediction error variance.
When `r`

is a matrix, `e`

is a column
vector. The number of rows of `e`

is the same as
the number of columns of `r`

.

[1] Proakis, John G., and Dimitris G. Manolakis. *Digital
Signal Processing: Principles, Algorithms, and Applications*.
3rd Edition. Upper Saddle River, NJ: Prentice-Hall, 1996, pp. 868–873.

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