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We derive finite time error bounds for estimating general linear time-invariant (LTI) systems from a single observed trajectory using the method of least squares.
Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters
TL Lai and CZ Wei · 1983
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Bounds for the smallest singular value of a jordan block with an application to eigenvalue perturbation
Jiang Erxiong · 1994
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Rates of convergence for empirical processes of stationary mixing sequences
Bin Yu · 1994
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Finite sample properties of system identification methods
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Eigenvalue and Singular Value Inequalities of Schur Complements
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A learning theory approach to system identification and stochastic adaptive control
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Singular vector autoregressions with deterministic terms: Strong consistency and lag order determination
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Finite time identification in unstable linear systems
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Theory and algorithms for forecasting time series
Vitaly Kuznetsov and Mehryar Mohri · 2018
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Non-asymptotic identification of lti systems from a single trajectory
Samet Oymak and Necmiye Ozay · 2018
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Learning without mixing: Towards a sharp analysis of linear system identification
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Inconsistent var regression with common explosive roots
Peter CB Phillips and Tassos Magdalinos · 2013
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High-dimensional probability: An introduction with applications in data science
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