gaussiankernel.hpp

dysii是一款非常出色的滤波函数库

#ifndef INDII_ML_AUX_GAUSSIANKERNEL_HPP
#define INDII_ML_AUX_GAUSSIANKERNEL_HPP

#include "Kernel.hpp"

namespace indii {
  namespace ml {
    namespace aux {
/**
 * Gaussian kernel for density estimation.
 *
 * @author Lawrence Murray <[e-mail]>
 * @version $Rev: 404 $
 * @date $Date: 2008-03-05 14:52:55 +0000 (Wed, 05 Mar 2008) $
 */
class GaussianKernel : public Kernel {
public:
  /**
   * Constructor.
   *
   * @param N \f$N\f$; dimensionality of the problem.
   * @param h \f$h\f$; the scaling parameter (bandwidth).
   *
   * Although the kernel itself is not intrinsically dependent on \f$N\f$
   * and \f$h\f$, its normalisation is. Supplying these allows substantial
   * performance increases through precalculationa.
   */
  GaussianKernel(const unsigned int N, const double h);

  virtual double operator()(const double x) const;

  /**
   * Sample from the kernel.
   *
   * @return A sample from the kernel.
   */
  virtual double sample() const;
  
private:
  /**
   * \f$h\f$; the scaling parameter (bandwidth).
   */
  double h;

  /**
   * \f$(h\sqrt{2\pi})^{-1}\f$; the normalisation term.
   */
  double ZI;
  
  /**
   * \f$(-2h^2)^{-1}\f$; the exponent term.
   */
  double E;

};

    }
  }
}

#include <math.h>

inline double indii::ml::aux::GaussianKernel::operator()(const double x)
    const {
  return ZI * exp(E * pow(x,2));
}

#endif