/*
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* Copyright (c) 2010-2019 Belledonne Communications SARL.
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*
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* This file is part of oRTP.
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program 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
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef ORTP_UTILS_H
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#define ORTP_UTILS_H
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#include "ortp/port.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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/**
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* Utility object to determine a maximum or minimum (but not both at the same
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* time), of a signal during a sliding period of time.
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*/
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typedef struct _OrtpExtremum{
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float current_extremum;
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float last_stable;
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uint64_t extremum_time;
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int period;
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}OrtpExtremum;
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ORTP_PUBLIC void ortp_extremum_reset(OrtpExtremum *obj);
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ORTP_PUBLIC void ortp_extremum_init(OrtpExtremum *obj, int period);
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/**
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* Record a new value for minimal.
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* @return TRUE if extremum has changed or false otherwise.
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*/
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ORTP_PUBLIC bool_t ortp_extremum_record_min(OrtpExtremum *obj, uint64_t curtime, float value);
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ORTP_PUBLIC bool_t ortp_extremum_record_max(OrtpExtremum *obj, uint64_t curtime, float value);
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ORTP_PUBLIC float ortp_extremum_get_current(OrtpExtremum *obj);
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/**
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* Unlike ortp_extremum_get_current() which can be very fluctuating, ortp_extremum_get_previous() returns the extremum found for the previous period.
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**/
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ORTP_PUBLIC float ortp_extremum_get_previous(OrtpExtremum *obj);
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/**
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* Utility object to interpolate linear model based on captures with 0-mean noise.
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* Based on the model (x, y) where y evolves depending on x with relation y = m*x+b,
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* it will estimate unknown values b, m using given noisy measures xmes and ymes, eg real
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* system is evolving with: y = m * x + b + noise.
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* Note: If noise is NOT white, the residue will be absorbed by one of the estimators.
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* It is an implementation of recursive least square algorithm, based on Kalman filter.
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*/
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typedef struct _OrtpKalmanRLS{
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/* Unknown parameters to estimate */
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double m, b;
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/* Gain matrix, must not be modified */
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double P[2][2];
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/** Forgetting factor in [94, .999]. Used when unknown parameters vary in time. **/
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double lambda;
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}OrtpKalmanRLS;
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ORTP_PUBLIC void ortp_kalman_rls_init(OrtpKalmanRLS *obj, double m0, double b0);
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ORTP_PUBLIC void ortp_kalman_rls_record(OrtpKalmanRLS *obj, double xmes, double ymes);
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typedef struct _OrtpBwEstimator{
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float one_minus_alpha;
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float inv_step;
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float exp_constant;
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struct timeval last_packet_recv;
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float value;
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}OrtpBwEstimator;
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/**
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* Utility object to compute a sliding exponential mean bitrate.
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* @param obj the estimator structure to initialize
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* @param alpha the weight of previous estimation (between 0 and 1)
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* @param step a time constant in seconds representing the sampling period
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**/
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ORTP_PUBLIC void ortp_bw_estimator_init(OrtpBwEstimator *obj, float alpha, float step);
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ORTP_PUBLIC void ortp_bw_estimator_packet_received (OrtpBwEstimator *obj, size_t bytes, const struct timeval *recv_time);
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ORTP_PUBLIC float ortp_bw_estimator_get_value(OrtpBwEstimator *obj);
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#ifdef __cplusplus
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}
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#endif
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#endif
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