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ELE
770 – Statistical Signal Processing Syllabus -
Spring 2023-2024 Course Description Basic
objective of the course is to give idea on fundamental principles of
statistical signal processing, knowledge of basic estimation, filtering,
prediction methods such as Bayes, MAP, MLE, LMSE, Wiener, Levinson, and
Kalman filters. Course Info Tuesday
13:30 - 16:20 E9
Classroom Documents
will be uploaded to the STAR system https://star.ee.hacettepe.edu.tr/ Lecturer Info Dr. Barış Yüksekkaya Office:
Department of Electrical and Electronics Engineering, New Building, 3rd Floor Office
Hours: Thursday 13:30-15:30 Tel:
0312 297 7000 E-mail:
byuksek {at}
ee. hacettepe. edu. tr Textbook and Materials 1-
Lecture Notes. 2- S.
Kay, Fundamentals of Statistical Signal Processing, Vol.I-II,
Prentice Hall. 3-
Statistical Signal Processing and Modeling, M. H. Hayes, Wiley. 4- T.
Moon and W. Stirling, Mathematical Methods and Algorithms for Signal
Processing, Prentice-Hall. 5-
S.J. Orfanidis, Optimum Signal Processing, McGraww Hill. Grading Homeworks 25% Midterm 25% Final 50% (In addition, a certain threshold must be obtained from the
Final Exam to be successful in the course.) Course Content 1. Norms, Orthogonal Spaces, Projections, Random
Vectors. 2. Orthogonal Projections, Gram-Schmidt
Orthogonalization. 3. Random Processes, Gaussian Processes, Markov
Processes. 4. Random State Models. 5. Analysis of Systems, Spectral Factorization,
Rational Modeling. 6. Bayesian Estimation, MAP, MLE,MSE. 7. LMSE. 8. Wiener Filter. 9. Levinson Filter. 10. Kalman Filter Rules Attendance
is recommended. Failure
to enter the midterm and to submit the homeworks
will result in F1 grade. Failure
to enter the final exam will result in F2 grade. In
order to be successful in the course, a certain base score must be obtained
from the final exam. |
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