ECE 5412

ECE 5412

Course information provided by the Courses of Study 2017-2018.

Course covering Bayesian inference for stochastic systems, parameter estimation and Bayesian networks. Includes optimal Bayesian filtering including Kalman filter, Hidden Markov model filter, sequential Monte-Carlo (particle) filters; maximum likelihood parameter estimation including the EM algorithm; social learning models and inference; Bayesian networks and their applications. The course will emphasize applications in social systems/networks, sensing and communication systems.

When Offered Spring.

  • Students will learn state of the art methods in Bayesian state estimation, parameter estimation and applications.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits GradeNoAud

  • 17284ECE 5412  LEC 030

  • Taught in NYC. Enrollment limited to Cornell Tech students. *Weill students must obtain instructor approval to enroll. Please send completed registration forms and instructor approval to Add/drop dates: January 16th at 8 a.m. to February 7th at 4 p.m. Students will only be registered if space allows.