lti::hiddenMarkovModel::singleDensity Class Reference

This class represents a single multivariate (ie multidimensional ) score density function within a state of a hidden markov model. More...

#include <ltiHiddenMarkovModel.h>

Inheritance diagram for lti::hiddenMarkovModel::singleDensity:

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Collaboration diagram for lti::hiddenMarkovModel::singleDensity:

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List of all members.

Public Member Functions
	singleDensity ()
	singleDensity (const singleDensity &other)
virtual	~singleDensity ()
singleDensity &	copy (const singleDensity &other)
singleDensity &	operator= (const singleDensity &other)
const char *	getTypeName () const
virtual bool	write (ioHandler &handler, const bool complete=true) const
virtual bool	read (ioHandler &handler, const bool complete=true)
Public Attributes
double	weightScore
dvector	mean
dvector	scalingFactor

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Detailed Description

This class represents a single multivariate (ie multidimensional ) score density function within a state of a hidden markov model.

The dimensions of the density function are assumed to be independent of each other.

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Constructor & Destructor Documentation

lti::hiddenMarkovModel::singleDensity::singleDensity

(

)

default constructor

lti::hiddenMarkovModel::singleDensity::singleDensity

(

const singleDensity &

other

)

copy constructor

Parameters:

other

the object to be copied

virtual lti::hiddenMarkovModel::singleDensity::~singleDensity

(

)

[virtual]

destructor

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Member Function Documentation

singleDensity& lti::hiddenMarkovModel::singleDensity::copy

(

const singleDensity &

other

)

copy data of "other" singleDensity.

Please note that the status string will _NOT_ be copied!

Reimplemented from lti::ioObject.

const char* lti::hiddenMarkovModel::singleDensity::getTypeName

(

)

const [virtual]

returns name of this type

Reimplemented from lti::ioObject.

singleDensity& lti::hiddenMarkovModel::singleDensity::operator=

(

const singleDensity &

other

)

assigment operator (alias for copy(other)).

Parameters:

other

the singleDensity to be copied

Returns:

a reference to the actual ioObject

Reimplemented from lti::ioObject.

virtual bool lti::hiddenMarkovModel::singleDensity::read	(	ioHandler &	handler,
		const bool	complete = true
	)			[virtual]

read the parameters from the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::ioObject.

virtual bool lti::hiddenMarkovModel::singleDensity::write	(	ioHandler &	handler,
		const bool	complete = true
	)			const [virtual]

write the parameters in the given ioHandler

Parameters:

	handler	the ioHandler to be used
	complete	if true (the default) the enclosing begin/end will be also written, otherwise only the data block will be written.

Returns:

true if write was successful

Reimplemented from lti::ioObject.

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Member Data Documentation

dvector lti::hiddenMarkovModel::singleDensity::mean

The mean vector.

In other words the center of this density function.

dvector lti::hiddenMarkovModel::singleDensity::scalingFactor

Scaling factor vector.

The scaling factor is a generic term for the spread of a density function. For example in gaussian functions it is known as the standard deviation.

double lti::hiddenMarkovModel::singleDensity::weightScore

The densities weight expressed as score.

The weight score is -ln(w), where w would be the corresponding probability associated with this single density.

The weights are required in mixture densities, which consist of several single densities, to rate the contribution of each single density. The sum over all weights w in a mixture density must be one.

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The documentation for this class was generated from the following file:

• ltiHiddenMarkovModel.h