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authorttt2018-05-04 14:17:52 +0530
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-function [a,varargout] = ac2poly(r)
-// Convert autocorrelation sequence to polynomial of prediction filter
-//
-// Calling Sequence
-// a = ac2poly(r)
-// [a,e] = ac2poly(r)
-//
-// Parameters
-// r: Autocorrelation sequence to be represented with an FIR linear prediction filter
-// a: Output polynomial representing the linear prediction filter e/(a(1) + a(2)z + a(3)z^2 .. a(N)z^N-1)
-// e: Output scaling for the lienar prediction filter
-//
-// Description
-// Function ac2poly() finds the best fit polynomial for FIR linear prediction filter a, corresponding to the autocorrelation sequence r. a is the same length as r, and is normalized with the first element. So a(1) = 1.
-// Author:
-// Parthe Pandit
-//
-// Bibliography
-// Kay, Steven M. Modern Spectral Estimation. Englewood Cliffs, NJ: Prentice-Hall, 1988.
-
-//errcheck
-if (type(r) > 1) then
- error('Input autocorrelation sequence needs to be of type double');
-end
-
-[a,e] = levinson(r);
-varargout = list(e);
-
-endfunction