2.160 | Spring 2006 | Graduate

Identification, Estimation, and Learning


Students are required to complete one project, which counts towards 20% of their final grade.


Find a project topic of your interest. Use identification, estimation, and learning techniques relevant to the course material. Possible topics include, but are not limited to:

  • Online and Offline System Identification
  • Parameter Estimation
  • Kalman Filtering
  • Neural Networks
  • Wavelet Transformation
  • Learning Control
  • Adaptive Control
  • Model Structure Selection
  • Experiment Design

A good term project will contain a mixture of theory and practice. Please include an interesting context or application background, address how you achieved the goal, and discuss specific technical details. Don’t forget that the focus of this subject is data; let the data speak about the system.


The project should be a maximum of ten pages long, excluding figures. Please include a title, name, and an abstract. The paper should contain the following sections:

  • Introduction: Objective, Background, Review, etc.
  • Issues and Methodology
  • Numerical/Experimental Results and Discussion
  • Conclusion
  • References