/* * linear least squares model * * Copyright (c) 2006 Michael Niedermayer * * This file is part of Libav. * * Libav is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * Libav is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with Libav; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #ifndef AVUTIL_LLS_H #define AVUTIL_LLS_H #include "macros.h" #include "mem.h" #include "version.h" #define MAX_VARS 32 #define MAX_VARS_ALIGN FFALIGN(MAX_VARS+1,4) //FIXME avoid direct access to LLSModel from outside /** * Linear least squares model. */ typedef struct LLSModel { DECLARE_ALIGNED(32, double, covariance[MAX_VARS_ALIGN][MAX_VARS_ALIGN]); DECLARE_ALIGNED(32, double, coeff[MAX_VARS][MAX_VARS]); double variance[MAX_VARS]; int indep_count; /** * Take the outer-product of var[] with itself, and add to the covariance matrix. * @param m this context * @param var training samples, starting with the value to be predicted * 32-byte aligned, and any padding elements must be initialized * (i.e not denormal/nan). */ void (*update_lls)(struct LLSModel *m, double *var); /** * Inner product of var[] and the LPC coefs. * @param m this context * @param var training samples, excluding the value to be predicted. unaligned. * @param order lpc order */ double (*evaluate_lls)(struct LLSModel *m, double *var, int order); } LLSModel; void avpriv_init_lls(LLSModel *m, int indep_count); void ff_init_lls_x86(LLSModel *m); void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order); #endif /* AVUTIL_LLS_H */