Faculty of Electrical Engineering

Czech Technical University in Prague

CTU in Prague

Subject description - B2M31ADA

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B2M31ADA Adaptive signal processing Extent of teaching:2p+2c
Guarantors:Bortel R. Roles:PV,V Completion:Z,ZK
Teachers:Sovka P.
Responsible Department:13131 Credits:5 Semester:Z

Anotation:

This course provides a basic discourse on adaptive algorithms for filtering, decorrelation, separation and beamforming. The course explains adaptive algorithms for estimation and prediction, including analysis, implementation and practical applications. Next, it describes the algorithms for adaptive decorrelation and separation of multidimensional signals. Last, the course provides analysis of adaptive beamforming techniques.

Study targets:

This course aims to provides the basic knowledge in the area of algorithms for filtering, decorrelation, separation and beamforming.

Course outlines:

1. Block algorithms for estimation
2. Block algorithms for prediction
3. LMS and RLS algorithms and their use for estimation and prediction
4. Convergence of LMS and RLS algorithms
5. Structures for implementation of adaptive filters
6. Use of adaptive algorithms for signal compression
7. Use of adaptive algorithms for noise suppression
8. Kalman filters
9. Grid filters and particle filters
10. Adaptive algorithms for decorrelation of multidimensional signals
11. Adaptive algorithms for separation of multidimensional signals
12. Adaptive beamforming - LCMV and MVDR algorithms
13. Adaptive beamforming - MUSIC algorithm
14. Reserved

Exercises outline:

1. Implementation of block algorithms for estimation
2. Implementation of block algorithms for prediction
3. Implementation of LMS and RLS algorithms
4. Convergence of LMS and RLS algorithms
5. Comparisoin of structures for implementation of adaptive filters
6. Vocoder
7. Adaptive supression of narrowband interference.
8. Application of Kalman filters
9. Use of grid filters and particle filters
10. Implementation of algorithms for decorrelation of multidimensional signals
11. Implementation of algorithms for separation of multidimensional signals
12. Application of LCMV and MVDR algorithms
13. Application of MUSIC algorithm
14. Reserved

Literature:

Sayed, A.H., Adaptive Filters, Wiley-IEEE Press, 2008. Bellanger, M.B., Adaptive Digital Filters, Marcel Dekker, NY 2001. Hyvarinen, A, Karhunen, J, Oja, E. Independent Component Analysis, John Wiley & Sons, 2004.

Requirements:

The knowledge of basic digital signal processing techniques - primarily the spectral analysis and non-adaptive linear filtering. Ability to use Matlab.

Keywords:

adaptive filtering, LMS and RLS algorithms, blind separation, beamforming

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 3


Page updated 19.10.2017 17:48:42, semester: L/2016-7, Z,L/2017-8, Z/2018-9, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)
Responsible person: doc. Ing. Jiří Jakovenko, Ph.D.