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Date
2024-01-19Type
- Conference Paper
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Abstract
This tutorial serves as an introduction to recently developed non-asymptotic methods in the theory of-mainly linear-system identification. We emphasize tools we deem particularly useful for a range of problems in this domain, such as the covering technique, the Hanson-Wright Inequality and the method of self-normalized martingales. We then employ these tools to give streamlined proofs of the performance of various least-squares based estimators for identifying the parameters in autoregressive models. We conclude by sketching out how the ideas presented herein can be extended to certain nonlinear identification problems. Show more
Publication status
publishedExternal links
Book title
2023 62nd IEEE Conference on Decision and Control (CDC)Pages / Article No.
Publisher
IEEEEvent
Organisational unit
00002 - ETH Zürich
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ETH Bibliography
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