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Approximate system identification: Misfit versus latency
This video was recorded at Workshop on Approximate Inference in Stochastic Processes and Dynamical Systems, Cumberland Lodge 2008. Two fundamentally different approaches in system identification, which are used for quantification of the model–data mismatch, are misfit and latency. The aim of this talk is to explain the rationale behind them and link them to statistical estimation methods—errors-in-variables regression and classical regression—respectively.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
