filter.hpp

dysii是一款非常出色的滤波函数库

#ifndef INDII_ML_FILTER_FILTER_HPP
#define INDII_ML_FILTER_FILTER_HPP

#include "../aux/vector.hpp"
#include "../aux/GaussianPdf.hpp"

namespace indii {
  namespace ml {
    namespace filter {
/**
 * Abstract %filter.
 *
 * @author Lawrence Murray <[e-mail]>
 * @version $Rev: 344 $
 * @date $Date: 2007-11-02 20:21:05 +0000 (Fri, 02 Nov 2007) $
 *
 * @param T The type of time.
 * @param P The type of probability distribution used to represent the
 * system state. 
 * 
 * @see indii::ml::filter for general usage guidelines.
 */
template <class T = unsigned int, class P = indii::ml::aux::GaussianPdf>
class Filter {
public:
  /**
   * Constructor.
   *
   * @param p_x0 \f$P\big(\mathbf{x}(0)\big)\f$; prior over the initial state
   * \f$\mathbf{x}(0)\f$.
   */
  Filter(const P& p_x0);

  /**
   * Destructor.
   */
  virtual ~Filter();

  /**
   * Get the current time.
   *
   * @return \f$t_n\f$; the current time.
   */
  T getTime() const;

  /**
   * Set the current time.
   *
   * @param tn \f$t_n\f$; the current time.
   */
  void setTime(const T tn);

  /**
   * Get distribution over the state at the current time given past
   * and present measurements.
   *
   * @return \f$P\big(\mathbf{x}(t_n)\, |
   * \,\mathbf{y}(t_1),\ldots,\mathbf{y}(t_n)\big)\f$; distribution
   * over the current state given past and present measurements.
   */
  P& getFilteredState();

  /**
   * Set the distribution over the state at the current time given
   * past and present measurements.
   *
   * @param p_xtn_ytn \f$P\big(\mathbf{x}(t_n)\, |
   * \,\mathbf{y}(t_1),\ldots,\mathbf{y}(t_n)\big)\f$; distribution
   * over the current state given past and present measurements.
   */
  void setFilteredState(const P& p_xtn_ytn);

  /**
   * Advance system to time of next measurement.
   *
   * @param tnp1 \f$t_{n+1}\f$; the time to which to advance the
   * system. This must be greater than the current time \f$t_n\f$.
   * @param ytnp1 \f$\mathbf{y}(t_{n+1})\f$; measurement at time
   * \f$t_{n+1}\f$.
   */
  virtual void filter(T tnp1, const indii::ml::aux::vector& ytnp1) = 0;

  /**
   * Apply the measurement function to the current filtered state to
   * obtain an estimated measurement.
   *
   * @return The estimated measurement.
   */
  virtual P measure() = 0;

protected:
  /**
   * \f$t_n\f$; the current time. For internal use only.
   */
  T tn;

  /**
   * \f$P\big(\mathbf{x}(t_n)\, |
   * \,\mathbf{y}(t_1),\ldots,\mathbf{y}(t_n)\big)\f$; distribution
   * over the current state given past and present measurements. For
   * internal use only.
   */
  P p_xtn_ytn;

};

    }
  }
}

using namespace indii::ml::filter;

template <class T, class P>
Filter<T,P>::Filter(const P& p_x0) : p_xtn_ytn(p_x0) {
  this->tn = 0;
}

template <class T, class P>
Filter<T,P>::~Filter() {
  //
}

template <class T, class P>
T Filter<T,P>::getTime() const {
  return this->tn;
}

template <class T, class P>
void Filter<T,P>::setTime(const T tn) {
  this->tn = tn;
}

template <class T, class P>
P& Filter<T,P>::getFilteredState() {
  return this->p_xtn_ytn;
}

template <class T, class P>
void Filter<T,P>::setFilteredState(const P& p_xtn_ytn) {
  this->p_xtn_ytn = p_xtn_ytn;
}

#endif