ac2poly
Transformation of an autocorrelation sequence into a predictive filter polynomial.
| Library |
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Arguments
Input arguments
# ac — autocorrelation sequence
+
vector | the matrix
Details
An autocorrelation sequence given as a vector or matrix.
If you specify an argument ac as a matrix, the function ac2poly will consider each column ac as a separate channel.
| Data types |
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| Support for complex numbers |
Yes |
Output arguments
# a — coefficients of the predictive filter
+
vector | the matrix
Details
Coefficients of the predictive filter returned as a string vector with the same number of elements as in the argument ac, or in the form of a matrix with as many rows as channels are defined in the argument ac. The function returns the first column a How 1, thus a[1] = 1 if a is a string vector.
Polynomial a represents the coefficients of a predictive filter that outputs a signal with an autocorrelation sequence approximately equal to ac.
# eFinal — power of finite prediction error
+
scalar
Details
The power of the final prediction error, returned as a scalar.
Examples
Polynomial of a predictive filter based on an autocorrelation sequence
Details
Let an autocorrelation sequence be given ac, we define an equivalent polynomial of a linear predictive filter and a finite prediction error.
import EngeeDSP.Functions: ac2poly
ac = [5.0000 -1.5450 -3.9547 3.9331 1.4681 -4.7500]
a, efinal = ac2poly(ac)
println("a = ", a, "\neFinal = ", efinal)a = [1.0 0.6147394267420019 0.9898137123620191 0.00042096865645934855 0.003444720005228037 -0.007709673467442522]
eFinal = 0.17914515163827727