Statistical Signal Processing

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Radioelectronics

Synopsis:

Parameter estimation and detection theory. General properties and

fundamental limits. ML, LS, Bayes (MAP,MSE), NP, MM estimators and

detectors. Adaptive filter theory (Kalman, RLS). Iterative detection and

parameter estimation.

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

Study materials:

[1] S. M. Kay: Fundamentals of statistical signal processing, vol I+II, 1993, 1998, Prentice-Hall

[2] A. H. Sayed: Fundamentals of Adaptive filtering, Wiley-interscience, 2003

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Doctoral studies, daily studies (compulsory elective course)
• Doctoral studies, combined studies (compulsory elective course)
• Doctoral studies, structured daily studies (compulsory elective course)
• Doctoral studies, structured combined studies (compulsory elective course)