0
(
ratings
)
students
Created by:
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
5
5
Instructor Rating
1
Reviews
1520
Courses
1916
Students
Massachusetts Institute of Technology
