ref: c77b96333b471c7b8a89852ee941e6a8987751b4
dir: /silk/SKP_Silk_stereo_find_predictor.c/
/*********************************************************************** Copyright (c) 2006-2011, Skype Limited. All rights reserved. Redistribution and use in source and binary forms, with or without modification, (subject to the limitations in the disclaimer below) 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 Skype Limited, nor the names of specific contributors, may be used to endorse or promote products derived from this software without specific prior written permission. NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE. 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. ***********************************************************************/ #include "SKP_Silk_main.h" /* Find least-squares prediction gain for one signal based on another and quantize it */ SKP_int32 SKP_Silk_stereo_find_predictor( /* O Returns predictor in Q13 */ const SKP_int16 x[], /* I Basis signal */ const SKP_int16 y[], /* I Target signal */ SKP_int length /* I Number of samples */ ) { SKP_int scale, scale1, scale2; SKP_int32 nrg1, nrg2, corr, pred_Q13; /* Find predictor */ SKP_Silk_sum_sqr_shift( &nrg1, &scale1, x, length ); SKP_Silk_sum_sqr_shift( &nrg2, &scale2, y, length ); if( scale1 > scale2 ) { scale = scale1; } else { scale = scale2; nrg1 = SKP_RSHIFT32( nrg1, scale2 - scale1 ); } corr = SKP_Silk_inner_prod_aligned_scale( x, y, scale, length ); pred_Q13 = SKP_DIV32_varQ( corr, SKP_max( nrg1, 1 ), 13 ); pred_Q13 = SKP_LIMIT( pred_Q13, -SKP_FIX_CONST( 10, 13 ), SKP_FIX_CONST( 10, 13 ) ); return pred_Q13; }