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

FREE
This course includes
Hours of videos

277 years, 9 months

Units & Quizzes

10

Unlimited Lifetime access
Access on mobile app
Certificate of Completion

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 Currilcum

  • 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