Moderate Deviations for System Identification: Error Bounds from a Probability Concentration Perspective
نویسندگان
چکیده
This paper is devoted to moderate deviations for characterizing parameter estimation errors in system identification. Moderate deviations for system identification provide probabilistic error bounds that are beyond laws of large numbers and central limit theorems, and cannot be expressed in terms of large deviations bounds. Such error bounds are crucial in complexity analysis for system identification. Explicit error bounds are derived and their relations to identification complexity analysis are explored. Examples are included to illustrate the ideas and results of this paper.
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