Minimax identification of a nonlinear dynamic observation system

Minimax optimization of the estimate of parameters of a nonlinear observation model containing random errors with unknown covariance matrices is investigated. An iteration algorithm for computing the minimax estimate is designed and its convergence is demonstrated. Theoretical results are tested by concrete examples.

Presented by the member of Editorial Board: A. I. Kibzun