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lls.h
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1 /*
2  * linear least squares model
3  *
4  * Copyright (c) 2006 Michael Niedermayer <michaelni@gmx.at>
5  *
6  * This file is part of FFmpeg.
7  *
8  * FFmpeg is free software; you can redistribute it and/or
9  * modify it under the terms of the GNU Lesser General Public
10  * License as published by the Free Software Foundation; either
11  * version 2.1 of the License, or (at your option) any later version.
12  *
13  * FFmpeg is distributed in the hope that it will be useful,
14  * but WITHOUT ANY WARRANTY; without even the implied warranty of
15  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
16  * Lesser General Public License for more details.
17  *
18  * You should have received a copy of the GNU Lesser General Public
19  * License along with FFmpeg; if not, write to the Free Software
20  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
21  */
22 
23 #ifndef AVUTIL_LLS_H
24 #define AVUTIL_LLS_H
25 
26 #include "macros.h"
27 #include "mem.h"
28 #include "version.h"
29 
30 #define MAX_VARS 32
31 #define MAX_VARS_ALIGN FFALIGN(MAX_VARS+1,4)
32 
33 //FIXME avoid direct access to LLSModel from outside
34 
35 /**
36  * Linear least squares model.
37  */
38 typedef struct LLSModel {
41  double variance[MAX_VARS];
43  /**
44  * Take the outer-product of var[] with itself, and add to the covariance matrix.
45  * @param m this context
46  * @param var training samples, starting with the value to be predicted
47  * 32-byte aligned, and any padding elements must be initialized
48  * (i.e not denormal/nan).
49  */
50  void (*update_lls)(struct LLSModel *m, const double *var);
51  /**
52  * Inner product of var[] and the LPC coefs.
53  * @param m this context
54  * @param var training samples, excluding the value to be predicted. unaligned.
55  * @param order lpc order
56  */
57  double (*evaluate_lls)(struct LLSModel *m, const double *var, int order);
58 } LLSModel;
59 
61 void ff_init_lls_x86(LLSModel *m);
62 void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order);
63 
64 #endif /* AVUTIL_LLS_H */
double covariance[(((32+1)+(4)-1)&~((4)-1))][(((32+1)+(4)-1)&~((4)-1))]
Definition: lls.h:39
Linear least squares model.
Definition: lls.h:38
Memory handling functions.
double variance[MAX_VARS]
Definition: lls.h:41
#define DECLARE_ALIGNED(n, t, v)
Declare a variable that is aligned in memory.
Definition: mem.h:111
Utility Preprocessor macros.
#define MAX_VARS_ALIGN
Definition: lls.h:31
Libavutil version macros.
typedef void(APIENTRY *FF_PFNGLACTIVETEXTUREPROC)(GLenum texture)
#define MAX_VARS
Definition: lls.h:30
double(* evaluate_lls)(struct LLSModel *m, const double *var, int order)
Inner product of var[] and the LPC coefs.
Definition: lls.h:57
void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order)
Definition: lls.c:47
double coeff[32][32]
Definition: lls.h:40
void(* update_lls)(struct LLSModel *m, const double *var)
Take the outer-product of var[] with itself, and add to the covariance matrix.
Definition: lls.h:50
int indep_count
Definition: lls.h:42
void avpriv_init_lls(LLSModel *m, int indep_count)
Definition: lls.c:115
void ff_init_lls_x86(LLSModel *m)
Definition: lls_init.c:31