### Abstract

The problem of parameters estimation in the dynamic matrix of a linear system described by stochastic differential equations is considered. The measurements of the states of the system are supposed to be distorted by the additive white Gaussian noise. The sequential estimates which ensure the estimation of the unknown parameters and their linear combinations with the given accuracy (in mean square sense) are being constructed. A sequence of these estimates converges almost surely (a. s. ) and in mean square sense. The results may be applied to the identification of dynamic systems, in adaptive filtering and control.

Original language | English |
---|---|

Pages (from-to) | 101-112 |

Number of pages | 12 |

Journal | Problems of control and information theory |

Volume | 16 |

Issue number | 2 |

Publication status | Published - 1987 |

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### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Problems of control and information theory*,

*16*(2), 101-112.

**SEQUENTIAL IDENTIFICATION OF LINEAR DYNAMIC SYSTEMS IN CONTINUOUS TIME BY NOISY OBSERVATIONS.** / Vasiliev, V. A.; Konev, V. V.

Research output: Contribution to journal › Article

*Problems of control and information theory*, vol. 16, no. 2, pp. 101-112.

}

TY - JOUR

T1 - SEQUENTIAL IDENTIFICATION OF LINEAR DYNAMIC SYSTEMS IN CONTINUOUS TIME BY NOISY OBSERVATIONS.

AU - Vasiliev, V. A.

AU - Konev, V. V.

PY - 1987

Y1 - 1987

N2 - The problem of parameters estimation in the dynamic matrix of a linear system described by stochastic differential equations is considered. The measurements of the states of the system are supposed to be distorted by the additive white Gaussian noise. The sequential estimates which ensure the estimation of the unknown parameters and their linear combinations with the given accuracy (in mean square sense) are being constructed. A sequence of these estimates converges almost surely (a. s. ) and in mean square sense. The results may be applied to the identification of dynamic systems, in adaptive filtering and control.

AB - The problem of parameters estimation in the dynamic matrix of a linear system described by stochastic differential equations is considered. The measurements of the states of the system are supposed to be distorted by the additive white Gaussian noise. The sequential estimates which ensure the estimation of the unknown parameters and their linear combinations with the given accuracy (in mean square sense) are being constructed. A sequence of these estimates converges almost surely (a. s. ) and in mean square sense. The results may be applied to the identification of dynamic systems, in adaptive filtering and control.

UR - http://www.scopus.com/inward/record.url?scp=0023207747&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0023207747&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0023207747

VL - 16

SP - 101

EP - 112

JO - Problems of control and information theory

JF - Problems of control and information theory

SN - 0370-2529

IS - 2

ER -