103302b375
commit 5b64cf7c4d67af9050bc959996ef976ce6326888
Author: Jean-Marc Valin <jean-marc.valin@octasic.com>
Date: Thu May 19 16:40:35 2011 -0400
Fixes a few bugs introduced in the latest update
commit b91eb86025d2de3c4cf04f4fb1aa48a28ad676a3
Author: Timothy B. Terriberry <tterribe@xiph.org>
Date: Thu May 19 16:12:02 2011 -0400
build_draft.sh fixes
commit 0b10c30db7ad60ff7d4bfc1139bdb86e0543c035
Author: Jean-Marc Valin <jean-marc.valin@octasic.com>
Date: Thu May 19 15:30:21 2011 -0400
Fixes the draft build
commit 164424cded5978e657105104e171ac202dde5e5b
Author: Jean-Marc Valin <jean-marc.valin@octasic.com>
Date: Thu May 19 15:00:23 2011 -0400
Updated build system
commit 188d9fcba8c3a1b1ad67c67c430e1b37e3658a40
Author: Koen Vos <koen.vos@skype.net>
Date: Thu May 19 17:14:57 2011 -0400
SILK/Opus update
203 lines
9 KiB
C
203 lines
9 KiB
C
/***********************************************************************
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Copyright (c) 2006-2011, Skype Limited. All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, (subject to the limitations in the disclaimer below)
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are permitted provided that the following conditions are met:
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- Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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- Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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- Neither the name of Skype Limited, nor the names of specific
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contributors, may be used to endorse or promote products derived from
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this software without specific prior written permission.
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NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED
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BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
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CONTRIBUTORS ''AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
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BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
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NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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***********************************************************************/
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#include "silk_main_FLP.h"
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#include "silk_tuning_parameters.h"
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/**********************************************************************
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* LDL Factorisation. Finds the upper triangular matrix L and the diagonal
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* Matrix D (only the diagonal elements returned in a vector)such that
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* the symmetric matric A is given by A = L*D*L'.
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**********************************************************************/
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void silk_LDL_FLP(
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SKP_float *A, /* (I/O) Pointer to Symetric Square Matrix */
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SKP_int M, /* (I) Size of Matrix */
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SKP_float *L, /* (I/O) Pointer to Square Upper triangular Matrix */
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SKP_float *Dinv /* (I/O) Pointer to vector holding the inverse diagonal elements of D */
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);
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/**********************************************************************
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* Function to solve linear equation Ax = b, when A is a MxM lower
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* triangular matrix, with ones on the diagonal.
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**********************************************************************/
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void silk_SolveWithLowerTriangularWdiagOnes_FLP(
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const SKP_float *L, /* (I) Pointer to Lower Triangular Matrix */
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SKP_int M, /* (I) Dim of Matrix equation */
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const SKP_float *b, /* (I) b Vector */
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SKP_float *x /* (O) x Vector */
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);
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/**********************************************************************
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* Function to solve linear equation (A^T)x = b, when A is a MxM lower
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* triangular, with ones on the diagonal. (ie then A^T is upper triangular)
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**********************************************************************/
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void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP(
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const SKP_float *L, /* (I) Pointer to Lower Triangular Matrix */
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SKP_int M, /* (I) Dim of Matrix equation */
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const SKP_float *b, /* (I) b Vector */
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SKP_float *x /* (O) x Vector */
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);
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/**********************************************************************
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* Function to solve linear equation Ax = b, when A is a MxM
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* symmetric square matrix - using LDL factorisation
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**********************************************************************/
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void silk_solve_LDL_FLP(
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SKP_float *A, /* I/O Symmetric square matrix, out: reg. */
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const SKP_int M, /* I Size of matrix */
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const SKP_float *b, /* I Pointer to b vector */
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SKP_float *x /* O Pointer to x solution vector */
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)
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{
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SKP_int i;
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SKP_float L[ MAX_MATRIX_SIZE ][ MAX_MATRIX_SIZE ];
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SKP_float T[ MAX_MATRIX_SIZE ];
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SKP_float Dinv[ MAX_MATRIX_SIZE ]; // inverse diagonal elements of D
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SKP_assert( M <= MAX_MATRIX_SIZE );
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/***************************************************
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Factorize A by LDL such that A = L*D*(L^T),
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where L is lower triangular with ones on diagonal
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****************************************************/
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silk_LDL_FLP( A, M, &L[ 0 ][ 0 ], Dinv );
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/****************************************************
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* substitute D*(L^T) = T. ie:
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L*D*(L^T)*x = b => L*T = b <=> T = inv(L)*b
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******************************************************/
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silk_SolveWithLowerTriangularWdiagOnes_FLP( &L[ 0 ][ 0 ], M, b, T );
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/****************************************************
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D*(L^T)*x = T <=> (L^T)*x = inv(D)*T, because D is
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diagonal just multiply with 1/d_i
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****************************************************/
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for( i = 0; i < M; i++ ) {
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T[ i ] = T[ i ] * Dinv[ i ];
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}
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/****************************************************
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x = inv(L') * inv(D) * T
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*****************************************************/
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silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP( &L[ 0 ][ 0 ], M, T, x );
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}
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void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP(
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const SKP_float *L, /* (I) Pointer to Lower Triangular Matrix */
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SKP_int M, /* (I) Dim of Matrix equation */
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const SKP_float *b, /* (I) b Vector */
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SKP_float *x /* (O) x Vector */
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)
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{
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SKP_int i, j;
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SKP_float temp;
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const SKP_float *ptr1;
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for( i = M - 1; i >= 0; i-- ) {
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ptr1 = matrix_adr( L, 0, i, M );
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temp = 0;
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for( j = M - 1; j > i ; j-- ) {
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temp += ptr1[ j * M ] * x[ j ];
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}
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temp = b[ i ] - temp;
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x[ i ] = temp;
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}
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}
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void silk_SolveWithLowerTriangularWdiagOnes_FLP(
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const SKP_float *L, /* (I) Pointer to Lower Triangular Matrix */
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SKP_int M, /* (I) Dim of Matrix equation */
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const SKP_float *b, /* (I) b Vector */
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SKP_float *x /* (O) x Vector */
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)
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{
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SKP_int i, j;
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SKP_float temp;
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const SKP_float *ptr1;
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for( i = 0; i < M; i++ ) {
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ptr1 = matrix_adr( L, i, 0, M );
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temp = 0;
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for( j = 0; j < i; j++ ) {
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temp += ptr1[ j ] * x[ j ];
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}
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temp = b[ i ] - temp;
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x[ i ] = temp;
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}
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}
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void silk_LDL_FLP(
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SKP_float *A, /* (I/O) Pointer to Symetric Square Matrix */
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SKP_int M, /* (I) Size of Matrix */
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SKP_float *L, /* (I/O) Pointer to Square Upper triangular Matrix */
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SKP_float *Dinv /* (I/O) Pointer to vector holding the inverse diagonal elements of D */
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)
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{
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SKP_int i, j, k, loop_count, err = 1;
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SKP_float *ptr1, *ptr2;
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double temp, diag_min_value;
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SKP_float v[ MAX_MATRIX_SIZE ], D[ MAX_MATRIX_SIZE ]; // temp arrays
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SKP_assert( M <= MAX_MATRIX_SIZE );
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diag_min_value = FIND_LTP_COND_FAC * 0.5f * ( A[ 0 ] + A[ M * M - 1 ] );
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for( loop_count = 0; loop_count < M && err == 1; loop_count++ ) {
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err = 0;
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for( j = 0; j < M; j++ ) {
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ptr1 = matrix_adr( L, j, 0, M );
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temp = matrix_ptr( A, j, j, M ); // element in row j column j
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for( i = 0; i < j; i++ ) {
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v[ i ] = ptr1[ i ] * D[ i ];
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temp -= ptr1[ i ] * v[ i ];
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}
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if( temp < diag_min_value ) {
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/* Badly conditioned matrix: add white noise and run again */
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temp = ( loop_count + 1 ) * diag_min_value - temp;
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for( i = 0; i < M; i++ ) {
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matrix_ptr( A, i, i, M ) += ( SKP_float )temp;
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}
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err = 1;
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break;
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}
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D[ j ] = ( SKP_float )temp;
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Dinv[ j ] = ( SKP_float )( 1.0f / temp );
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matrix_ptr( L, j, j, M ) = 1.0f;
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ptr1 = matrix_adr( A, j, 0, M );
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ptr2 = matrix_adr( L, j + 1, 0, M);
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for( i = j + 1; i < M; i++ ) {
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temp = 0.0;
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for( k = 0; k < j; k++ ) {
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temp += ptr2[ k ] * v[ k ];
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}
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matrix_ptr( L, i, j, M ) = ( SKP_float )( ( ptr1[ i ] - temp ) * Dinv[ j ] );
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ptr2 += M; // go to next column
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}
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}
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}
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SKP_assert( err == 0 );
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}
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