Subject description - BE2M31DSPA

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BE2M31DSPA Digital Signal Processing
Roles:PS, PV, P Extent of teaching:2P+2C
Department:13131 Language of teaching:EN
Guarantors:Pollák P. Completion:Z,ZK
Lecturers:Pollák P. Credits:6
Tutors:Pollák P. Semester:Z

Web page:

https://moodle.fel.cvut.cz/courses/BE2M31DSPA

Anotation:

The subject gives overview about basic methods of digital signal processing and their applications (examples from speech and biological signal processing): disrete-time signals and systems, signal characteristics in time and frequency domain, Fourier transform, fast algorithms for DFT computation, introduction to digital filter design, digital filtering in time and frequency domain, decimation and interpolation and their usage in filter banks, basics of LPC analysis. Further details can be found at <a href=http://noel.feld.cvut.cz/vyu/be2m31dspa>;http://noel.feld.cvut.cz/vyu/be2m31dspa<;/a> .

Study targets:

Students should acquire theoretical and practical experiences about basic DSP techniques and the most frequent applications. Simple implementations and simulations of basic DSP methods in MATLAB environment are solved in seminars of the subject.

Course outlines:

1. Introduction to DSP. Sampling theorem.
2. Basic characteristics of digital signals.
3. Autocorrelation and crosscorrelation functions
4. Fourier transform of discrete signal.
5. Properties of DFT, fast algorithms for DFT computation.
6. Spectral characteristics of stachastic and non-stationary signals.
7. Signal and system reprezentation in Z-domain
8. Digital Filtering I - FIR filters.
9. Digital filtering II - IIR filters.
10. Digital filtering in the frequency domain.
11. Basics of multi-band signal processing.
12. Basics of parametric methods of signal processing.
13. DSP applications in speech and biological signal processing. Signal compression.
14. Reserve.

Exercises outline:

1. Introduction to MATLAB and other tools
2. Computation of basic time-domain characterstics in MATLAB
3. Autocorrelation analysis and its applications
4. Discrete Fourier Transform (DFT) and its properties, interpolation, zero-padding
5. Spectral analysis of deterministic signals
6. Spectral analysis of stochastic and non-stationary signals
7. Discrete-time systems: basic properties, frequency repsonse
8. Design of digital FIR filters
9. Design of digital IIR filters
10. Digital filtering in frequency domain
11. Implementation of signal segmentation (OLA, OLS)Parametric metods of DSP
12. Basics of multi-band signal processing
13. Parametric metods of DSP
14. Reserve

Literature:

[1] Oppenheim, A.V., Shafer, R.W.: Discrete-Time Signal Processing. 3rd edition. Prentice-Hall, 2009
[2] Vaseghi S.V..: Advanced Digital Signal Processing and Noise Reduction. 4th edition. Wiley, 2008
[3] The MathWorks: MATLAB User's and Reference Guides.
(Any other book devoted to digital signal processing.)

Requirements:

Bases of signal and system theory with necessary mathematical background are supposed as preliminary knowledge.

Keywords:

discrete-time signal, digital signal, DFT, autocorrelation, spectral analysis, digital systems, digital filtering, linear predictive analysis

Subject is included into these academic programs:

Program Branch Role Recommended semester
MEEK6_2018 Mobile Communications P 1
MEBIO3_2018 Image Processing PV 2
MEEK3_2018 Photonics P 1
MEEK4_2018 Technology of the Internet of Things P 1
MEEK7_2018 Radio Systems P 1
MEEK5_2018 Communication Systems and Networks P 1
MEBIO4_2018 Signal Processing PS 2
MEEK2_2018 Audiovisual Technology and Signal Processing P 1
MEBIO2_2018 Medical Instrumentation PV 2
MEBIO1_2018 Bioinformatics PV 2
MEEK1_2018 Electronics P 1


Page updated 18.4.2024 17:51:04, semester: L/2023-4, Z/2024-5, Z/2023-4, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)