Subject description - B2M37SSP

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B2M37SSP Statistical Signal Processing Extent of teaching:4P+0C
Guarantors:Sýkora J. Roles:PV,V Language of
teaching:
CS
Teachers:Sovka P., Sýkora J. Completion:ZK
Responsible Department:13137 Credits:5 Semester:L

Anotation:

The course provides fundamentals in three main domains of the statistical signal processing: 1) estimation theory, 2) detection theory, 3) optimal and adaptive filtering. The statistical signal processing is a core theory with many applications ranging from digital communications, audio and video processing, radar and radio navigation, measurement and experiment evaluation, etc.

Course outlines:

1. Estimation
1a. MVU estimator, Cramer-Rao lower bound, composite hypothesis, performance criteria 1b. Sufficient statistics 1c. Maximum Likelihood estimator, EM algorithm 1d. Bayesian estimators (MMSE, MAP)
2. Detection
2a. Hypothesis testing (binary, multiple, composite) 2b. Deterministic signals 2c. Random signals
3. Optimal and adaptive Filtration
3a. Signal modeling (ARMA, Padé approximation, ...) 3b. Toeplitz equation, Levinson-Durbin recursion 3c. MMSE filters, Wiener filter. 3d. Kalman filter. 3e. Least Squares, RLS 3f. Steepest descent and stochastic gradient algorithms. 3g. Spectrum estimation

Exercises outline:

Literature:

1. Steven Kay: Fundamentals of Statistical Signal Processing - Estimation theory
2. Steven Kay: Fundamentals of Statistical Signal Processing - Detection theory
3. Monson Hayes: Statistical digital signal processing and modeling
4. Ali Sayed: Fundamentals of Adaptive Filtering
5. S. M. Kay: Fundamentals of statistical signal processing-detection theory, Prentice-Hall 1998

Requirements:

Subject is included into these academic programs:

Program Branch Role Recommended semester
MPEK3_2016 Electronics V
MPEK1_2016 Communication Systems and Networks V
MPEK2_2016 Radio and Optical Technology V
MPEK4_2016 Media and Signal Processing PV 2


Page updated 19.9.2019 17:53:02, semester: Z,L/2020-1, L/2018-9, Z,L/2019-20, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)