zeus::TStochasticProcess Class Reference

#include <StochasticProcess.h>

List of all members.

Public Member Functions
	TStochasticProcess (const IMatrix &rMatrix)
virtual	~TStochasticProcess ()
bool	isValid () const
TVector	getProbabilities (const IVector &rSource, Int iRuns=1) const
TVector	getLongTermProbabilities (const IVector &rSource) const
Float	getLongTermEntropy () const
Float	getConditionalEntropy (Int iSteps=1) const

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Detailed Description

The stochastic process class implements the Markov chain used to calculate time dependend propabilities. The implementation works on time invariant or homogeneous Markov sources.

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Constructor & Destructor Documentation

TStochasticProcess::TStochasticProcess

(

const IMatrix &

rMatrix )

Creates a stochastic process

TStochasticProcess::~TStochasticProcess

(

)

[virtual]

Destroys the stochastic process

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Member Function Documentation

Float TStochasticProcess::getConditionalEntropy

(

Int

iSteps = 1 )

const

Returns the conditional uncertainty of the process. The cond. uncertainty is the entropy rate of the chain.

Float zeus::TStochasticProcess::getLongTermEntropy

(

)

const [inline]

returns the long time uncertainty of the stochastic process

TVector TStochasticProcess::getLongTermProbabilities

(

const IVector &

rSource )

const

Gets the longterm probability distribution (PI)

TVector TStochasticProcess::getProbabilities	(	const IVector &	rSource,
		Int	iRuns = 1
	)		const

Returns the target propability vector after n runs

Parameters:

rSource	: Source propabilites
iRuns	: Number of runs

Returns:

Target propabilities

bool TStochasticProcess::isValid

(

)

const

Checks if the transformation matrix of the stochastic process is valid

Return values:

true	: matrix is valid
false,:	matrix is not a transformation matrix

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

• StochasticProcess.h
• StochasticProcess.cpp