com.numericalmethod.suanshu.stats.hmm.mixture

Class HmmViterbi

java.lang.Object

com.numericalmethod.suanshu.stats.hmm.mixture.HmmViterbi

All Implemented Interfaces:

java.io.Serializable

public class HmmViterbi
extends java.lang.Object
implements java.io.Serializable

The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states – called the Viterbi path – that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models.

See Also:

• Rabiner, L.R. "A tutorial on hidden Markov models and selected applications in speech recognition," Proceedings of the IEEE. Volume 77, Issue 2, 257 - 286. Feb 1989.
• W. Zucchini and I. L. MacDonald, "Hidden Markov Models for Time Series: An Introduction Using R," Boca Raton, Florida, CRC Press, 2009.
• Wikipedia: Viterbi algorithm

, Serialized Form

Constructor Summary

Constructors

Constructor and Description
HmmViterbi(HiddenMarkovModel model) Construct an Viterbi algorithm for an HMM.

Method Summary

Modifier and Type	Method and Description
int[]	getViterbiStates(double[] observations) Generate the most likely sequence of states by using Viterbi algorithm (global decoding), given the observations and the parameters of the underlying hidden Markov model.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

HmmViterbi

public HmmViterbi(HiddenMarkovModel model)

Construct an Viterbi algorithm for an HMM.

Parameters:

model - the underlying hidden Markov model

Method Detail

getViterbiStates

public int[] getViterbiStates(double[] observations)

Generate the most likely sequence of states by using Viterbi algorithm (global decoding), given the observations and the parameters of the underlying hidden Markov model.

Parameters:

observations - the observations

Returns:

the most likely sequence of states