25 #ifndef __ADAPTWINPOLYESTIMATOR_H__
26 #define __ADAPTWINPOLYESTIMATOR_H__
30 #include <yarp/sig/Vector.h>
85 yarp::sig::Vector
mse;
97 virtual yarp::sig::Vector
fit(
const yarp::sig::Vector &
x,
98 const yarp::sig::Vector &
y,
const unsigned int n=0);
105 virtual double eval(
double x);
122 AWPolyEstimator(
unsigned int _order,
unsigned int _N,
const double _D);
191 virtual yarp::sig::Vector
fit(
const yarp::sig::Vector &
x,
192 const yarp::sig::Vector &
y,
const unsigned int n=0);
Adaptive window linear fitting to estimate the first derivative.
virtual yarp::sig::Vector fit(const yarp::sig::Vector &x, const yarp::sig::Vector &y, const unsigned int n=0)
Redefine method to improve computation just for first-order estimator.
AWLinEstimator(unsigned int _N, const double _D)
virtual double getEsteeme()
Return the current estimation.
Basic element for adaptive polynomial fitting.
AWPolyElement()
Default constructor.
AWPolyElement(const yarp::sig::Vector &d, const double t)
Create an element for adaptive polynomial fitting.
Adaptive window polynomial fitting.
yarp::sig::Vector estimate()
Execute the algorithm upon the elements list, with the max deviation threshold given by D.
AWPolyList & getList()
Return a reference to internal elements list.
void feedData(const AWPolyElement &el)
Feed data into the algorithm.
yarp::sig::Vector getMSE()
Return the mean squared error (MSE) computed over the current windows lengths between the predictions...
virtual ~AWPolyEstimator()
Destructor.
virtual double eval(double x)
Evaluate regressor at certain point.
void reset()
Reinitialize the internal state.
virtual double getEsteeme()=0
Return the current estimation.
yarp::sig::Vector getWinLen()
Return the current windows lengths.
AWPolyEstimator(unsigned int _order, unsigned int _N, const double _D)
Create a polynomial estimator object of order _order on an adaptive window of a maximum length _N an ...
virtual yarp::sig::Vector fit(const yarp::sig::Vector &x, const yarp::sig::Vector &y, const unsigned int n=0)
Find the regressor which best fits in least square sense the last n data sample couples,...
Adaptive window quadratic fitting to estimate the second derivative.
virtual double getEsteeme()
Return the current estimation.
AWQuadEstimator(unsigned int _N, const double _D)
std::deque< AWPolyElement > AWPolyList
This file contains the definition of unique IDs for the body parts and the skin parts of the robot.