From 6011540ce239922c0723ff2f1534e915b420cd1f Mon Sep 17 00:00:00 2001 From: Sunil Shetye Date: Tue, 17 Jul 2018 18:02:33 +0530 Subject: remove autogenerated files remove execute permission from scilab files update macros/names fix build process by building macros before help --- help/en_US/scilab_en_US_help/poly2ac.html | 92 ------------------------------- 1 file changed, 92 deletions(-) delete mode 100644 help/en_US/scilab_en_US_help/poly2ac.html (limited to 'help/en_US/scilab_en_US_help/poly2ac.html') diff --git a/help/en_US/scilab_en_US_help/poly2ac.html b/help/en_US/scilab_en_US_help/poly2ac.html deleted file mode 100644 index 27abf6c..0000000 --- a/help/en_US/scilab_en_US_help/poly2ac.html +++ /dev/null @@ -1,92 +0,0 @@ - - - poly2ac - - - -
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- << pmusic - - - FOSSEE Signal Processing Toolbox - - - poly2lsf >> - -
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- - - - FOSSEE Signal Processing Toolbox >> FOSSEE Signal Processing Toolbox > poly2ac - -

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poly2ac

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Convert prediction polynomial to autocorrelation sequence.

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Calling Sequence

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R = poly2ac(a,efinal)
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Parameters

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a: -

input prediction polynomial with 1st element 1 (if not, poly2ac normalizes it to 1 before proceeding).

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efinal: -

input prediction error

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r: -

output autocorrelation sequence

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Description

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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)

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Examples

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a = [1.0000 0.4288 0.76 0.0404 -0.02];
-efinal = 0.2;           // Step prediction error
-r = poly2ac(a,efinal)   // Autocorrelation sequence
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See also

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Bibliography

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S. Kay, Modern Spectral Estimation, Prentice Hall, N.J., 1987, Chapter 6.

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