1 files changed, 63 insertions, 0 deletions
diff --git a/media/ffvpx/libavutil/lls.h b/media/ffvpx/libavutil/lls.h
new file mode 100644
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+++ b/media/ffvpx/libavutil/lls.h
@@ -0,0 +1,63 @@
+/*
+ * linear least squares model
+ *
+ * Copyright (c) 2006 Michael Niedermayer <michaelni@gmx.at>
+ *
+ * This file is part of FFmpeg.
+ *
+ * FFmpeg 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.
+ *
+ * FFmpeg 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 FFmpeg; 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_internal.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, const 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, const 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 */