### Abstract

The simultaneous estimation of the state sequence of a discrete-time finite-state Markov chain and the unknown probabilities governing the Markov chain is considered. The availability of discrete observations made in the presence of memoryless noise is assumed. A decision-directed estimator based on the Viterbi algorithm using the true Markov chain probabilities is described.

Original language | English (US) |
---|---|

Title of host publication | Proceedings of the IEEE Conference on Decision and Control |

Publisher | IEEE |

Pages | 2278-2279 |

Number of pages | 2 |

State | Published - 1987 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Chemical Health and Safety
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality

### Cite this

*Proceedings of the IEEE Conference on Decision and Control*(pp. 2278-2279). IEEE.

**DECISION DIRECTED ESTIMATION OF THE STATE SEQUENCE OF AN UNKNOWN MARKOV CHAIN.** / Morrell, Darryl; Stirling, Wynn.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the IEEE Conference on Decision and Control.*IEEE, pp. 2278-2279.

}

TY - GEN

T1 - DECISION DIRECTED ESTIMATION OF THE STATE SEQUENCE OF AN UNKNOWN MARKOV CHAIN.

AU - Morrell, Darryl

AU - Stirling, Wynn

PY - 1987

Y1 - 1987

N2 - The simultaneous estimation of the state sequence of a discrete-time finite-state Markov chain and the unknown probabilities governing the Markov chain is considered. The availability of discrete observations made in the presence of memoryless noise is assumed. A decision-directed estimator based on the Viterbi algorithm using the true Markov chain probabilities is described.

AB - The simultaneous estimation of the state sequence of a discrete-time finite-state Markov chain and the unknown probabilities governing the Markov chain is considered. The availability of discrete observations made in the presence of memoryless noise is assumed. A decision-directed estimator based on the Viterbi algorithm using the true Markov chain probabilities is described.

UR - http://www.scopus.com/inward/record.url?scp=0023541419&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0023541419&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0023541419

SP - 2278

EP - 2279

BT - Proceedings of the IEEE Conference on Decision and Control

PB - IEEE

ER -