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Last updated:

August 6, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior;

time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.

Course Curriculum

  • Review of Linear Systems, Review of Stochastic Processes, Defining a General Framework Unlimited
  • Introductory Examples for System Identification Unlimited
  • Nonparametric Identification Unlimited
  • Least Squares, Statistical Properties Unlimited
  • Parameter Estimation Methods, Minimum Prediction Error Paradigm, Maximum Likelihood Unlimited
  • Convergence and Consistency, Informative Data, Convergence to the True Parameters Unlimited
  • Asymptotic Distribution of PEM Unlimited
  • Instrumental Variable Methods, Identification in Closed Loop, Asymptotic Results Unlimited
  • Computation, Levinson Algorithm, Recursive Estimation Unlimited
  • Identification in Practice, Error Filtering, Order Estimation, Model Structure Validation, Examples Unlimited

About the instructor

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Instructor Rating

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Reviews

1520

Courses

1915

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Massachusetts Institute of Technology