On the Role of Constraints in System Identification
نویسنده
چکیده
System identification is concerned with the estimation of parameters characterizing an unknown system. The estimation is usually based on observations of the system’s (possibly noisy) input(s) and output(s). In the so-called “blind” system identification scenario, the estimation is based on the observed output(s) only, aided by some general knowledge about statistical properties of the input(s), rather than by actual observations thereof. Quite commonly, the discussion is limited to discrete-time systems, assumed to be linear and time-invariant (LTI), stable and causal. As such, their input-output relation can always1 be described as
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