Functional series modeling approach to identification of nonstationary stochastic systems

The problem of identification of a nonstationary stochastic system is considered, and an estimation method based on the functional series modeling (FSM) of the system parameter trajectory is proposed for its solution. It is shown that the parameter-matching properties of FSM estimators can be described in terms of the appropriately defined (time-varying) impulse and frequency responses. It is suggested and verified by means of computer simulation that the averaged frequency characteristics associated with FSM estimators can yield useful information about their parameter-matching abilities.<
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