LSLLearning

class LSLLearning : public tsa::AlgoBase

rithm for the learning phase of the Adaptive Least Squares Lattice

Setters

inline void Load(const char *filename, const char *fmt = "txt")
inline void Save(const char *filename, const char *fmt = "txt")
inline void xml_serialize(eternity::xml_archive &xml, const char *p)

Operations

void operator()(SeqViewDouble &InputData, SeqViewDouble &WhitenedData)
Parameters:

  • InputData – Time series

  • WhitenedData – Whitened Time series

void operator()(SeqViewDouble &InputData, LatticeView &LatView)
Parameters:

  • InputData –

  • LatView –

void operator()(SeqViewDouble &InputData, Dvector &Parcor)
Parameters:

  • InputData –

  • Parcor –

void execute(matrix_row<Dmatrix> InputData, matrix_row<Dmatrix> OutputData)
Parameters:

  • InputData – Input data

  • OutputData – Output data

Getters

inline unsigned int GetOrder()
inline double GetParcorForward(unsigned int j)
inline double GetParcorBackward(unsigned int j)
inline double GetErrorForward(unsigned int i, unsigned int j)
inline double GetErrorBackward(unsigned int i, unsigned int j)
inline double GetEpf(unsigned int i, unsigned int j)
inline double GetEpb(unsigned int i, unsigned int j)
inline double GetGamma(unsigned int j)
inline unsigned int GetStatus()
inline double GetSigma()

Public Functions

LSLLearning(unsigned int Order, double sigma, double lambda = 1.0)

Constructor

Parameters:

  • Order – Order of the filter

  • sigma – guessed value for the initial sigma

  • Lwsp – Lenght of workspace

  • lambda – forgetting factor

LSLLearning(const LSLLearning &from)

Copy constructor

Parameters:

from – The instance that must be copied

~LSLLearning()

Destructor

LSLLearning &operator=(const LSLLearning &from)

Assignement operator

Parameters:

from – The instance to be assigned from

Returns:

a reference to a new object