Many engineering problems involve parameter identifiability and/or parameter estimation. The main objective of this course is to provide students with concepts and methodologies for parameter identifiability and parameter estimation. Topics will include parameter identifiability, model selection, least squares, maximum likelihood and maximum a Posteriori methods for linear nonlinear parameter estimation. Applications to some practical problems are also discussed. Weekly hours: 3 Lecture hoursPrerequisite(s): ME 251 and ME 431 or permission of the instructor.
Many engineering problems involve parameter identifiability and/or parameter estimation. The main objective of this course is to provide students with concepts and methodologies for parameter identifiability and parameter estimation. Topics will include parameter identifiability, model selection, least squares, maximum likelihood and maximum a Posteriori methods for linear nonlinear parameter estimation. Applications to some practical problems are also discussed. Weekly hours: 3 Lecture hoursPrerequisite(s): ME 251 and ME 431 or permission of the instructor.
