Detection under the Bayesian philosophy: probability of error, risk, optimum detector.
Examples: deterministic and random signals.
The presentation of the theory will be illustrated with examples of application from signal processing and communications. These applications will be also explored in the assigned homework, which will include both theoretical development and programming tasks.
Teaching methods and workload
Lectures, homework exercises, self-study.
Compulsory attendance is the only requirement.
Assessment methods and criteria
In addition to Homework exercises, the student may choose between Final Take-home Exam (48 hours) or Project work. Homework exercises will count 40 % and Final Take-Home Exam or Project work will count 60 %. Grading: Pass (A or B) or fail.