mlib_SignalLPCAutoCorrelGetEnergy_S16_Adp man page on SunOS

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mlib_SignalLPCAutoCorrelGemediaLibmlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)

NAME
       mlib_SignalLPCAutoCorrelGetEnergy_S16,	mlib_SignalLPCAutoCorrelGetEn‐
       ergy_S16_Adp - return the energy of the input signal

SYNOPSIS
       cc [ flag... ] file... -lmlib [ library... ]
       #include <mlib.h>

       mlib_status mlib_SignalLPCAutoCorrelGetEnergy_S16(
	   mlib_s16 *engery, mlib_s32 escale, void *state);

       mlib_status mlib_SignalLPCAutoCorrelGetEnergy_S16_Adp(
	   mlib_s16 *engery, mlib_s32 *escale, void *state);

DESCRIPTION
       Each of the functions returns the energy of the input signal.

       In linear predictive coding (LPC) model, each speech sample  is	repre‐
       sented as a linear combination of the past M samples.

		      M
	      s(n) = SUM a(i) * s(n-i) + G * u(n)
		     i=1

       where  s(*)  is the speech signal, u(*) is the excitation signal, and G
       is the gain constants, M is the order of the linear prediction  filter.
       Given  s(*),  the  goal is to find a set of coefficient a(*) that mini‐
       mizes the prediction error e(*).

			     M
	      e(n) = s(n) - SUM a(i) * s(n-i)
			    i=1

       In autocorrelation method, the coefficients can be obtained by  solving
       following set of linear equations.

	       M
	      SUM a(i) * r(|i-k|) = r(k), k=1,...,M
	      i=1

       where

		    N-k-1
	      r(k) = SUM s(j) * s(j+k)
		     j=0

       are  the	 autocorrelation  coefficients of s(*), N is the length of the
       input speech vector. r(0) is the energy of the speech signal.

       Note that the autocorrelation matrix R is a Toeplitz matrix  (symmetric
       with  all  diagonal  elements  equal),  and the equations can be solved
       efficiently with Levinson-Durbin algorithm.

       See Fundamentals of Speech Recognition by Lawrence Rabiner  and	Biing-
       Hwang Juang, Prentice Hall, 1993.

       Note for functions with adaptive scaling (with _Adp postfix), the scal‐
       ing factor of the output data will be calculated based  on  the	actual
       data;  for  functions with non-adaptive scaling (without _Adp postfix),
       the user supplied scaling factor will be used and the  output  will  be
       saturated if necessary.

PARAMETERS
       Each function takes the following arguments:

       energy	 The energy of the input signal.

       escale	 The  scaling  factor  of the energy, where actual_data = out‐
		 put_data * 2**(-scaling_factor).

       state	 Pointer to the internal state structure.

RETURN VALUES
       Each function returns MLIB_SUCCESS if successful. Otherwise it  returns
       MLIB_FAILURE.

ATTRIBUTES
       See attributes(5) for descriptions of the following attributes:

       ┌─────────────────────────────┬─────────────────────────────┐
       │      ATTRIBUTE TYPE	     │	    ATTRIBUTE VALUE	   │
       ├─────────────────────────────┼─────────────────────────────┤
       │Interface Stability	     │Committed			   │
       ├─────────────────────────────┼─────────────────────────────┤
       │MT-Level		     │MT-Safe			   │
       └─────────────────────────────┴─────────────────────────────┘

SEE ALSO
       mlib_SignalLPCAutoCorrelInit_S16(3MLIB),		mlib_SignalLPCAutoCor‐
       rel_S16(3MLIB), mlib_SignalLPCAutoCorrelGetPARCOR_S16(3MLIB), mlib_Sig‐
       nalLPCAutoCorrelFree_S16(3MLIB), attributes(5)

SunOS 5.10			  mlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)
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