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