Applied Stochcastic Estimation

Catalog Search > Engineering/Engineering Technology > 16.687

Note: This course is not available for the current semester.

Course No: 16.687; Last Offered: No Data;

Course Description

Review of random processes and key elements of probability theory. State space description of systems and random processes, relation to frequency domain techniques. Numerical methods of continuous and discrete time random system modeling. Optimal Kalman filtering for discrete and continuous random systems. Sensitivity analysis. Design considerations in the face of model uncertainty, numerical instabilities, bad data. Optimal smoothing. Nonlinear filtering. Parameter identification. Applications throughout.

Prerequisites & Notes

  • Prerequisites:
  • Special Notes:
  • Credits: 3;

Questions About This Course?

Contact the Advising Center at 978-934-2474 or Continuing_Education@uml.edu

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