mlib_signallpcautocorrelgetenergy_f32(3mlib) [sunos man page]

mlib_SignalLPCAutoCorrelGetEnergy_F32(3MLIB)		    mediaLib Library Functions		      mlib_SignalLPCAutoCorrelGetEnergy_F32(3MLIB)

NAME

       mlib_SignalLPCAutoCorrelGetEnergy_F32 - return the energy of the input signal

SYNOPSIS

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

       mlib_status mlib_SignalLPCAutoCorrelGetEnergy_F32(mlib_f32 *engery, void *state);

DESCRIPTION

       The mlib_SignalLPCAutoCorrelGetEnergy_F32() function returns the energy of the input signal.

       In linear predictive coding (LPC) model, each speech sample is represented 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 fil-
       ter. Given s(*), the goal is to find a set of coefficient a(*) that minimizes 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.

PARAMETERS

       The function takes the following arguments:

       energy	       The energy of the input signal.

       state	       Pointer to the internal state structure.

RETURN VALUES

       The 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	     |Evolving			   |
       +-----------------------------+-----------------------------+
       |MT-Level		     |MT-Safe			   |
       +-----------------------------+-----------------------------+

SEE ALSO

       mlib_SignalLPCAutoCorrelInit_F32(3MLIB),  mlib_SignalLPCAutoCorrel_F32(3MLIB), mlib_SignalLPCAutoCorrelGetPARCOR_F32(3MLIB), mlib_SignalLP-
       CAutoCorrelFree_F32(3MLIB), attributes(5)

SunOS 5.10							    10 Nov 2004 		      mlib_SignalLPCAutoCorrelGetEnergy_F32(3MLIB)

mlib_SignalLPCAutoCorrel_F32(3MLIB)			    mediaLib Library Functions			       mlib_SignalLPCAutoCorrel_F32(3MLIB)

NAME

       mlib_SignalLPCAutoCorrel_F32 - perform linear predictive coding with autocorrelation method

SYNOPSIS

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

       mlib_status mlib_SignalLPCAutoCorrel_F32(mlib_f32 *coeff,
	    const mlib_f32 *signal, void *state);

DESCRIPTION

       The mlib_SignalLPCAutoCorrel_F32() function performs linear predictive coding with autocorrelation method.

       In linear predictive coding (LPC) model, each speech sample is represented 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 fil-
       ter. Given s(*), the goal is to find a set of coefficient a(*) that minimizes 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.

PARAMETERS

       The function takes the following arguments:

       coeff	 The linear prediction coefficients.

       signal	 The input signal vector.

       state	 Pointer to the internal state structure.

RETURN VALUES

       The 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_F32(3MLIB),     mlib_SignalLPCAutoCorrelGetEnergy_F32(3MLIB),    mlib_SignalLPCAutoCorrelGetPARCOR_F32(3MLIB),
       mlib_SignalLPCAutoCorrelFree_F32(3MLIB), attributes(5)

SunOS 5.11							    2 Mar 2007				       mlib_SignalLPCAutoCorrel_F32(3MLIB)