### 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 |
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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 |

### ASJC Scopus subject areas

- Engineering(all)

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## Cite this

Vasiliev, V. A., & Konev, V. V. (1987). SEQUENTIAL IDENTIFICATION OF LINEAR DYNAMIC SYSTEMS IN CONTINUOUS TIME BY NOISY OBSERVATIONS.

*Problems of control and information theory*,*16*(2), 101-112.