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Diffstat (limited to 'src/opus-1.0.2/silk/float/solve_LS_FLP.c')
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diff --git a/src/opus-1.0.2/silk/float/solve_LS_FLP.c b/src/opus-1.0.2/silk/float/solve_LS_FLP.c new file mode 100644 index 00000000..a4bb0525 --- /dev/null +++ b/src/opus-1.0.2/silk/float/solve_LS_FLP.c @@ -0,0 +1,207 @@ +/*********************************************************************** +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 "main_FLP.h" +#include "tuning_parameters.h" + +/********************************************************************** + * LDL Factorisation. Finds the upper triangular matrix L and the diagonal + * Matrix D (only the diagonal elements returned in a vector)such that + * the symmetric matric A is given by A = L*D*L'. + **********************************************************************/ +static inline void silk_LDL_FLP( + silk_float *A, /* I/O Pointer to Symetric Square Matrix */ + opus_int M, /* I Size of Matrix */ + silk_float *L, /* I/O Pointer to Square Upper triangular Matrix */ + silk_float *Dinv /* I/O Pointer to vector holding the inverse diagonal elements of D */ +); + +/********************************************************************** + * Function to solve linear equation Ax = b, when A is a MxM lower + * triangular matrix, with ones on the diagonal. + **********************************************************************/ +static inline void silk_SolveWithLowerTriangularWdiagOnes_FLP( + const silk_float *L, /* I Pointer to Lower Triangular Matrix */ + opus_int M, /* I Dim of Matrix equation */ + const silk_float *b, /* I b Vector */ + silk_float *x /* O x Vector */ +); + +/********************************************************************** + * Function to solve linear equation (A^T)x = b, when A is a MxM lower + * triangular, with ones on the diagonal. (ie then A^T is upper triangular) + **********************************************************************/ +static inline void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP( + const silk_float *L, /* I Pointer to Lower Triangular Matrix */ + opus_int M, /* I Dim of Matrix equation */ + const silk_float *b, /* I b Vector */ + silk_float *x /* O x Vector */ +); + +/********************************************************************** + * Function to solve linear equation Ax = b, when A is a MxM + * symmetric square matrix - using LDL factorisation + **********************************************************************/ +void silk_solve_LDL_FLP( + silk_float *A, /* I/O Symmetric square matrix, out: reg. */ + const opus_int M, /* I Size of matrix */ + const silk_float *b, /* I Pointer to b vector */ + silk_float *x /* O Pointer to x solution vector */ +) +{ + opus_int i; + silk_float L[ MAX_MATRIX_SIZE ][ MAX_MATRIX_SIZE ]; + silk_float T[ MAX_MATRIX_SIZE ]; + silk_float Dinv[ MAX_MATRIX_SIZE ]; /* inverse diagonal elements of D*/ + + silk_assert( M <= MAX_MATRIX_SIZE ); + + /*************************************************** + Factorize A by LDL such that A = L*D*(L^T), + where L is lower triangular with ones on diagonal + ****************************************************/ + silk_LDL_FLP( A, M, &L[ 0 ][ 0 ], Dinv ); + + /**************************************************** + * substitute D*(L^T) = T. ie: + L*D*(L^T)*x = b => L*T = b <=> T = inv(L)*b + ******************************************************/ + silk_SolveWithLowerTriangularWdiagOnes_FLP( &L[ 0 ][ 0 ], M, b, T ); + + /**************************************************** + D*(L^T)*x = T <=> (L^T)*x = inv(D)*T, because D is + diagonal just multiply with 1/d_i + ****************************************************/ + for( i = 0; i < M; i++ ) { + T[ i ] = T[ i ] * Dinv[ i ]; + } + /**************************************************** + x = inv(L') * inv(D) * T + *****************************************************/ + silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP( &L[ 0 ][ 0 ], M, T, x ); +} + +static inline void silk_SolveWithUpperTriangularFromLowerWdiagOnes_FLP( + const silk_float *L, /* I Pointer to Lower Triangular Matrix */ + opus_int M, /* I Dim of Matrix equation */ + const silk_float *b, /* I b Vector */ + silk_float *x /* O x Vector */ +) +{ + opus_int i, j; + silk_float temp; + const silk_float *ptr1; + + for( i = M - 1; i >= 0; i-- ) { + ptr1 = matrix_adr( L, 0, i, M ); + temp = 0; + for( j = M - 1; j > i ; j-- ) { + temp += ptr1[ j * M ] * x[ j ]; + } + temp = b[ i ] - temp; + x[ i ] = temp; + } +} + +static inline void silk_SolveWithLowerTriangularWdiagOnes_FLP( + const silk_float *L, /* I Pointer to Lower Triangular Matrix */ + opus_int M, /* I Dim of Matrix equation */ + const silk_float *b, /* I b Vector */ + silk_float *x /* O x Vector */ +) +{ + opus_int i, j; + silk_float temp; + const silk_float *ptr1; + + for( i = 0; i < M; i++ ) { + ptr1 = matrix_adr( L, i, 0, M ); + temp = 0; + for( j = 0; j < i; j++ ) { + temp += ptr1[ j ] * x[ j ]; + } + temp = b[ i ] - temp; + x[ i ] = temp; + } +} + +static inline void silk_LDL_FLP( + silk_float *A, /* I/O Pointer to Symetric Square Matrix */ + opus_int M, /* I Size of Matrix */ + silk_float *L, /* I/O Pointer to Square Upper triangular Matrix */ + silk_float *Dinv /* I/O Pointer to vector holding the inverse diagonal elements of D */ +) +{ + opus_int i, j, k, loop_count, err = 1; + silk_float *ptr1, *ptr2; + double temp, diag_min_value; + silk_float v[ MAX_MATRIX_SIZE ], D[ MAX_MATRIX_SIZE ]; /* temp arrays*/ + + silk_assert( M <= MAX_MATRIX_SIZE ); + + diag_min_value = FIND_LTP_COND_FAC * 0.5f * ( A[ 0 ] + A[ M * M - 1 ] ); + for( loop_count = 0; loop_count < M && err == 1; loop_count++ ) { + err = 0; + for( j = 0; j < M; j++ ) { + ptr1 = matrix_adr( L, j, 0, M ); + temp = matrix_ptr( A, j, j, M ); /* element in row j column j*/ + for( i = 0; i < j; i++ ) { + v[ i ] = ptr1[ i ] * D[ i ]; + temp -= ptr1[ i ] * v[ i ]; + } + if( temp < diag_min_value ) { + /* Badly conditioned matrix: add white noise and run again */ + temp = ( loop_count + 1 ) * diag_min_value - temp; + for( i = 0; i < M; i++ ) { + matrix_ptr( A, i, i, M ) += ( silk_float )temp; + } + err = 1; + break; + } + D[ j ] = ( silk_float )temp; + Dinv[ j ] = ( silk_float )( 1.0f / temp ); + matrix_ptr( L, j, j, M ) = 1.0f; + + ptr1 = matrix_adr( A, j, 0, M ); + ptr2 = matrix_adr( L, j + 1, 0, M); + for( i = j + 1; i < M; i++ ) { + temp = 0.0; + for( k = 0; k < j; k++ ) { + temp += ptr2[ k ] * v[ k ]; + } + matrix_ptr( L, i, j, M ) = ( silk_float )( ( ptr1[ i ] - temp ) * Dinv[ j ] ); + ptr2 += M; /* go to next column*/ + } + } + } + silk_assert( err == 0 ); +} + |