# A Tutorial on Concentration Bounds for System Identification

arXiv: https://arxiv.org/abs/1906.11395 · HTML: https://mlsanity.com/paper/1906.11395/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jun 2019.

## Built on by (most cited first, 19 of 19)

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## Abstract (arXiv)

We provide a brief tutorial on the use of concentration inequalities as they apply to system identification of state-space parameters of linear time invariant systems, with a focus on the fully observed setting. We draw upon tools from the theories of large-deviations and self-normalized martingales, and provide both data-dependent and independent bounds on the learning rate.