LSSOFilter.h

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#ifndef LSSOFILTER_H_
#define LSSOFILTER_H_

/** \addtogroup sigproc Signal processing methods */
/* @{ */



#include "AdaptiveFilter.h"
//! Base class for least squares filter with a single output value
/*!*****************************************************
 * Base class for Least-Square filters with a single output value
 * currently used for LMS and RLS filters, implements all virtual
 * functions from CAdaptiveFilters apart from AdaptFilter, which
 * depends on the functionality of the individual filter
 * 
 * 
 * *****************************************************/
class LSSOFilter : public AdaptiveFilter
  {
private:
  //! For single output values the weights can be stored in a vector
  gplib::rvec Weights;
public:
  //! The way to calculate the output is the same for all single output filters, we implement it here 
  virtual void CalcOutput(const gplib::rvec &Input, gplib::rvec &Output);
  //! For single channel output we can also just return the output as a double
  double CalcOutput(const gplib::rvec &Input)
    {
      gplib::rvec temp;
      CalcOutput(Input, temp);
      return temp(0);
    }
  //! Return the current set of weights
  const gplib::rvec &GetWeights()
    {
      return Weights;
    }
  //! Implement the abstract function from adaptive filter, in this case just another name for GetWeights
  virtual const gplib::rvec &GetWeightsAsVector()
    {
      return Weights;
    }
  //! Print the weights to output stream
  virtual void PrintWeights(std::ostream &output);
  //! The constructor only needs the filter length, outputsize for Adaptive filter is 1 
  LSSOFilter(const int filterlength);
  virtual ~LSSOFilter();
  //! We declare friend classes for easier access to the Weight vector
  friend class LMSCanceller;
  friend class RLSCanceller;
  friend class AMRLSCanceller;
  friend class WienerInterpolator;
  };
/* @} */
#endif /*CLSSOFILTER_H_*/

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