mirror of
https://github.com/Relintai/pandemonium_engine.git
synced 2024-12-23 12:26:59 +01:00
187 lines
7.7 KiB
C
187 lines
7.7 KiB
C
|
/***********************************************************************
|
||
|
Copyright (c) 2006-2011, Skype Limited. All rights reserved.
|
||
|
Redistribution and use in source and binary forms, with or without
|
||
|
modification, are permitted provided that the following conditions
|
||
|
are met:
|
||
|
- Redistributions of source code must retain the above copyright notice,
|
||
|
this list of conditions and the following disclaimer.
|
||
|
- Redistributions in binary form must reproduce the above copyright
|
||
|
notice, this list of conditions and the following disclaimer in the
|
||
|
documentation and/or other materials provided with the distribution.
|
||
|
- Neither the name of Internet Society, IETF or IETF Trust, nor the
|
||
|
names of specific contributors, may be used to endorse or promote
|
||
|
products derived from this software without specific prior written
|
||
|
permission.
|
||
|
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
||
|
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
||
|
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
|
||
|
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
||
|
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||
|
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||
|
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||
|
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||
|
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||
|
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
||
|
POSSIBILITY OF SUCH DAMAGE.
|
||
|
***********************************************************************/
|
||
|
|
||
|
#ifdef HAVE_CONFIG_H
|
||
|
#include "config.h"
|
||
|
#endif
|
||
|
|
||
|
#include "SigProc_FLP.h"
|
||
|
#include "tuning_parameters.h"
|
||
|
#include "define.h"
|
||
|
|
||
|
#define MAX_FRAME_SIZE 384 /* subfr_length * nb_subfr = ( 0.005 * 16000 + 16 ) * 4 = 384*/
|
||
|
|
||
|
/* Compute reflection coefficients from input signal */
|
||
|
silk_float silk_burg_modified_FLP( /* O returns residual energy */
|
||
|
silk_float A[], /* O prediction coefficients (length order) */
|
||
|
const silk_float x[], /* I input signal, length: nb_subfr*(D+L_sub) */
|
||
|
const silk_float minInvGain, /* I minimum inverse prediction gain */
|
||
|
const opus_int subfr_length, /* I input signal subframe length (incl. D preceding samples) */
|
||
|
const opus_int nb_subfr, /* I number of subframes stacked in x */
|
||
|
const opus_int D /* I order */
|
||
|
)
|
||
|
{
|
||
|
opus_int k, n, s, reached_max_gain;
|
||
|
double C0, invGain, num, nrg_f, nrg_b, rc, Atmp, tmp1, tmp2;
|
||
|
const silk_float *x_ptr;
|
||
|
double C_first_row[ SILK_MAX_ORDER_LPC ], C_last_row[ SILK_MAX_ORDER_LPC ];
|
||
|
double CAf[ SILK_MAX_ORDER_LPC + 1 ], CAb[ SILK_MAX_ORDER_LPC + 1 ];
|
||
|
double Af[ SILK_MAX_ORDER_LPC ];
|
||
|
|
||
|
silk_assert( subfr_length * nb_subfr <= MAX_FRAME_SIZE );
|
||
|
|
||
|
/* Compute autocorrelations, added over subframes */
|
||
|
C0 = silk_energy_FLP( x, nb_subfr * subfr_length );
|
||
|
silk_memset( C_first_row, 0, SILK_MAX_ORDER_LPC * sizeof( double ) );
|
||
|
for( s = 0; s < nb_subfr; s++ ) {
|
||
|
x_ptr = x + s * subfr_length;
|
||
|
for( n = 1; n < D + 1; n++ ) {
|
||
|
C_first_row[ n - 1 ] += silk_inner_product_FLP( x_ptr, x_ptr + n, subfr_length - n );
|
||
|
}
|
||
|
}
|
||
|
silk_memcpy( C_last_row, C_first_row, SILK_MAX_ORDER_LPC * sizeof( double ) );
|
||
|
|
||
|
/* Initialize */
|
||
|
CAb[ 0 ] = CAf[ 0 ] = C0 + FIND_LPC_COND_FAC * C0 + 1e-9f;
|
||
|
invGain = 1.0f;
|
||
|
reached_max_gain = 0;
|
||
|
for( n = 0; n < D; n++ ) {
|
||
|
/* Update first row of correlation matrix (without first element) */
|
||
|
/* Update last row of correlation matrix (without last element, stored in reversed order) */
|
||
|
/* Update C * Af */
|
||
|
/* Update C * flipud(Af) (stored in reversed order) */
|
||
|
for( s = 0; s < nb_subfr; s++ ) {
|
||
|
x_ptr = x + s * subfr_length;
|
||
|
tmp1 = x_ptr[ n ];
|
||
|
tmp2 = x_ptr[ subfr_length - n - 1 ];
|
||
|
for( k = 0; k < n; k++ ) {
|
||
|
C_first_row[ k ] -= x_ptr[ n ] * x_ptr[ n - k - 1 ];
|
||
|
C_last_row[ k ] -= x_ptr[ subfr_length - n - 1 ] * x_ptr[ subfr_length - n + k ];
|
||
|
Atmp = Af[ k ];
|
||
|
tmp1 += x_ptr[ n - k - 1 ] * Atmp;
|
||
|
tmp2 += x_ptr[ subfr_length - n + k ] * Atmp;
|
||
|
}
|
||
|
for( k = 0; k <= n; k++ ) {
|
||
|
CAf[ k ] -= tmp1 * x_ptr[ n - k ];
|
||
|
CAb[ k ] -= tmp2 * x_ptr[ subfr_length - n + k - 1 ];
|
||
|
}
|
||
|
}
|
||
|
tmp1 = C_first_row[ n ];
|
||
|
tmp2 = C_last_row[ n ];
|
||
|
for( k = 0; k < n; k++ ) {
|
||
|
Atmp = Af[ k ];
|
||
|
tmp1 += C_last_row[ n - k - 1 ] * Atmp;
|
||
|
tmp2 += C_first_row[ n - k - 1 ] * Atmp;
|
||
|
}
|
||
|
CAf[ n + 1 ] = tmp1;
|
||
|
CAb[ n + 1 ] = tmp2;
|
||
|
|
||
|
/* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
|
||
|
num = CAb[ n + 1 ];
|
||
|
nrg_b = CAb[ 0 ];
|
||
|
nrg_f = CAf[ 0 ];
|
||
|
for( k = 0; k < n; k++ ) {
|
||
|
Atmp = Af[ k ];
|
||
|
num += CAb[ n - k ] * Atmp;
|
||
|
nrg_b += CAb[ k + 1 ] * Atmp;
|
||
|
nrg_f += CAf[ k + 1 ] * Atmp;
|
||
|
}
|
||
|
silk_assert( nrg_f > 0.0 );
|
||
|
silk_assert( nrg_b > 0.0 );
|
||
|
|
||
|
/* Calculate the next order reflection (parcor) coefficient */
|
||
|
rc = -2.0 * num / ( nrg_f + nrg_b );
|
||
|
silk_assert( rc > -1.0 && rc < 1.0 );
|
||
|
|
||
|
/* Update inverse prediction gain */
|
||
|
tmp1 = invGain * ( 1.0 - rc * rc );
|
||
|
if( tmp1 <= minInvGain ) {
|
||
|
/* Max prediction gain exceeded; set reflection coefficient such that max prediction gain is exactly hit */
|
||
|
rc = sqrt( 1.0 - minInvGain / invGain );
|
||
|
if( num > 0 ) {
|
||
|
/* Ensure adjusted reflection coefficients has the original sign */
|
||
|
rc = -rc;
|
||
|
}
|
||
|
invGain = minInvGain;
|
||
|
reached_max_gain = 1;
|
||
|
} else {
|
||
|
invGain = tmp1;
|
||
|
}
|
||
|
|
||
|
/* Update the AR coefficients */
|
||
|
for( k = 0; k < (n + 1) >> 1; k++ ) {
|
||
|
tmp1 = Af[ k ];
|
||
|
tmp2 = Af[ n - k - 1 ];
|
||
|
Af[ k ] = tmp1 + rc * tmp2;
|
||
|
Af[ n - k - 1 ] = tmp2 + rc * tmp1;
|
||
|
}
|
||
|
Af[ n ] = rc;
|
||
|
|
||
|
if( reached_max_gain ) {
|
||
|
/* Reached max prediction gain; set remaining coefficients to zero and exit loop */
|
||
|
for( k = n + 1; k < D; k++ ) {
|
||
|
Af[ k ] = 0.0;
|
||
|
}
|
||
|
break;
|
||
|
}
|
||
|
|
||
|
/* Update C * Af and C * Ab */
|
||
|
for( k = 0; k <= n + 1; k++ ) {
|
||
|
tmp1 = CAf[ k ];
|
||
|
CAf[ k ] += rc * CAb[ n - k + 1 ];
|
||
|
CAb[ n - k + 1 ] += rc * tmp1;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if( reached_max_gain ) {
|
||
|
/* Convert to silk_float */
|
||
|
for( k = 0; k < D; k++ ) {
|
||
|
A[ k ] = (silk_float)( -Af[ k ] );
|
||
|
}
|
||
|
/* Subtract energy of preceding samples from C0 */
|
||
|
for( s = 0; s < nb_subfr; s++ ) {
|
||
|
C0 -= silk_energy_FLP( x + s * subfr_length, D );
|
||
|
}
|
||
|
/* Approximate residual energy */
|
||
|
nrg_f = C0 * invGain;
|
||
|
} else {
|
||
|
/* Compute residual energy and store coefficients as silk_float */
|
||
|
nrg_f = CAf[ 0 ];
|
||
|
tmp1 = 1.0;
|
||
|
for( k = 0; k < D; k++ ) {
|
||
|
Atmp = Af[ k ];
|
||
|
nrg_f += CAf[ k + 1 ] * Atmp;
|
||
|
tmp1 += Atmp * Atmp;
|
||
|
A[ k ] = (silk_float)(-Atmp);
|
||
|
}
|
||
|
nrg_f -= FIND_LPC_COND_FAC * C0 * tmp1;
|
||
|
}
|
||
|
|
||
|
/* Return residual energy */
|
||
|
return (silk_float)nrg_f;
|
||
|
}
|