ref: d3358b1d42f5092c42f45a68f1e53a16b5a6926f
dir: /silk/float/silk_burg_modified_FLP.c/
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#include "silk_SigProc_FLP.h"
#define MAX_FRAME_SIZE 384 // subfr_length * nb_subfr = ( 0.005 * 16000 + 16 ) * 4 = 384
#define MAX_NB_SUBFR 4
/* Compute reflection coefficients from input signal */
SKP_float silk_burg_modified_FLP( /* O returns residual energy */
SKP_float A[], /* O prediction coefficients (length order) */
const SKP_float x[], /* I input signal, length: nb_subfr*(D+L_sub) */
const SKP_int subfr_length, /* I input signal subframe length (including D preceeding samples) */
const SKP_int nb_subfr, /* I number of subframes stacked in x */
const SKP_float WhiteNoiseFrac, /* I fraction added to zero-lag autocorrelation */
const SKP_int D /* I order */
)
{
SKP_int k, n, s;
double C0, num, nrg_f, nrg_b, rc, Atmp, tmp1, tmp2;
const SKP_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 ];
SKP_assert( subfr_length * nb_subfr <= MAX_FRAME_SIZE );
SKP_assert( nb_subfr <= MAX_NB_SUBFR );
/* Compute autocorrelations, added over subframes */
C0 = silk_energy_FLP( x, nb_subfr * subfr_length );
SKP_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 );
}
}
SKP_memcpy( C_last_row, C_first_row, SILK_MAX_ORDER_LPC * sizeof( double ) );
/* Initialize */
CAb[ 0 ] = CAf[ 0 ] = C0 + WhiteNoiseFrac * C0 + 1e-9f;
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;
}
SKP_assert( nrg_f > 0.0 );
SKP_assert( nrg_b > 0.0 );
/* Calculate the next order reflection (parcor) coefficient */
rc = -2.0 * num / ( nrg_f + nrg_b );
SKP_assert( rc > -1.0 && rc < 1.0 );
/* 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;
/* 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;
}
}
/* Return residual energy */
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 ] = (SKP_float)(-Atmp);
}
nrg_f -= WhiteNoiseFrac * C0 * tmp1;
return (SKP_float)nrg_f;
}