System Identification: Regression Models

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This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and the sparse identification of nonlinear dynamics (SINDy).

This video was produced at the University of Washington
  1. Steve Brunton
  2. Control theory
  3. Machine learning
  4. Data science
  5. Dynamical systems
  6. Machine learning control
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Комментарии
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Steve Can we use Deep Learning for System Identification of Non-Linear Models? Like using LSTMs to model a plant of a quad rotor only from it's sensor data?

leotrisport
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The extended DMD is that the same thing as Koopman (i.e the Linear representation of Nonlinear systems as explained in the previous lecture)?

AdeyemiAlabi
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where can i find that image i want to include that in my presentation.

piyushhirapara