man pages section 3: Multimedia Library Functions
Updated: July 2014

## mlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)

### Name

mlib_SignalLPCAutoCorrelGetEnergy_S16, mlib_SignalLPCAutoCorrelGetEnergy_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 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 filter. 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.

Note for functions with adaptive scaling (with _Adp postfix), the scaling 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 = output_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