Digital Signal Processing

Topic outline

• BE2M31DSPA, BE2M31CZS - Digital Signal Processing
  

  BE2M31DSPA, BE2M31CZS - Digital Signal Processing

  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 http://noel.feld.cvut.cz/vyu/be2m31dspa . 
  

  • Conditions of subject passing URL
  • List of exam questions File
  • Table with the classification URL
• Lectures
  

  Lectures

  • Lecture scheduling for winter semester 2018/2019 URL
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    Lecture 1 - Introduction to the Course. Basic properties of digital signals.

  • ae2m99czs_pr0.pdf File
  • ae2m99czs_pr1_handout.pdf File
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    Lecture 2 - Advanced time-domain signal characteristics. Auto-correlation and cross-correlation function.

  • ae2m99czs_pr2_handout.pdf File
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    Lecture 3 - Fourier transform of discrete signals

  • ae2m99czs_pr3_handout.pdf File
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    Lecture 4 - Spectral Analysis of Stochastic and Non-Stationary Signals

  • handnotes_spectral_characteristics.pdf File
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    Lecture 5 - Signal and system representation in time and Z-domain. 

  • be2m31czs_pr6.pdf File
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    Lecture 6 - Basic and special digital filters (complex rezonator, 1st and 2nd order FIR and IIR filters, MA filters, comb filters)

  • be2m31dsp_pr6a_HANDOUT.pdf File
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    Lecture 7 - Properties and design of digital IIR filters (system discretization)

  • be2m31dsp_pr8_IIR_HANDOUT.pdf File
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    Lecture 8 - Properties and design of  FIR digital filters

  • be2m31dsp_pr7_FIR_HANDOUT.pdf File
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    Lecture 9 - Digital fitlering in frequency-domain. Cyclic convolution.  OLS and OLA technique.

  • There are no slides for this lecture - use your handnotes from the lecture.

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    Lecture 10 - OLA technique with general window. Spectral masking, weighting, subtraction.

  • There are no slides for this lecture - use your handnotes from the lecture.

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    Lecture 11 - Signal resampling. Basics of multi-band signal processing

  • There are no slides for this lecture - use your handnotes from the lecture.

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    Lecture 12 - Signal resampling and filter banks
    

  • There are no slides for this lecture - use your handnotes from the lecture.

• Exercises
  

  Exercises

  • Exercise scheduling for winter semester 2018/2019 URL
  • MATLAB - CTU FEE Classkit license URL
  • b2m31czs_signaly.zip (archive with signals for all seminars) File
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    Exercise 1 -  Introduction to the Course. Signal Modeling 

    - Practical introduction into MATLAB environmet 
    - Basic time-domain signal characteristic

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • cv1_part1.m (generation of deterministic and random signals) File
  • cv1_part2.m (generation of noisy sinusoid) File
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    Exercise 2 - Correlation Analysis and Periodicity in the Signal 

    - Estimation of autocorrelation function 
    - Detection of signal periodicity in the time-domain

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • cv2_part1.m (basic estimations of ACF) File
  • cv2_part2.m (ACF of speech and musical instruments, detection of periodicity/pitch) File
  • cv2_part3.m (CCF and delay detection in GPS signals) File
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    Exercise 3 - Spectral analysis using DFT 

    DFT (FFT), main features - frequency resolution, spectral leakage (signal weigthing) 

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • • MATLAB solution
      • cv3_dft_part1.m
      • cv3_dft_part2.m
      • cv3_dft_part3.m
      • cv3_FTs_by_DFT.m
  • ———————————————————

    Exercise 4 -  Spectral Characteristics of Stochastic and Non-Stationary Signals

    - Short-time and long-time characteristics
    - PSD - Power Spectral Density

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • cv4_psd_spectrograms.m (PSD estimation, spectrograms of non-stationary signals) File
  • cv4_pwelch_scaling.m File
  • ———————————————————

    Exercise 5 - Discrete-time domain systems of the 1st order

    - Difference equation, transfer function, impulse response, frequency response.

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • cv5_discrete_systems1.m (discrete systems of the 1st order) File
  • ———————————————————

    Exercise 6 - Discrete-time domain systems of higher orders

    - Difference equation, transfer function, impulse response, frequency response.

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • cv5_discrete_systems2.m (discrete systems of higher orders) File
  • ———————————————————

    Exercise 7 - Design of  IIR digital filters 

    IIR filters, properties, design techniques in MATLAB, filtering realization

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • speech_8_16_44.mat File
  • cv_filtry_IIR.m (basic IIR filter design) File
  • ———————————————————

    Exercise 8 -  Design of  digital FIR Filters

    - FIR filter design in MATLAB, properties, filtering

  • Practical excercise in MATLAB URL
  • BACKUP SEMINAR GUIDELINES (when WEB-server noel is not available) Page
  • speech_8_16_44.mat File
  • cv_filtry_FIR.m (design of FIR filters) File
  • ———————————————————

    Exercise 9 - Design of Optimum Digital Filters

    - Tolerance scheme, MATLAB tools for optimum digital filter design

  • Practical excercise in MATLAB URL
  • cv_filtry_optimum.m (Design of FIR and IIR filters from tolerance scheme, non-linear phase) File
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    Exercise 10 -  Digital fitlering in the frequency-domain I

    - Implementation of cyclic convolution
    - OLA and OLS techniques

  • Practical excercise in MATLAB URL
  • cv_cyklicka_konvoluce.m (linear and cyclic convolution, overlap-and-save, overlap-and-add) File
  • cv_cyklicka_konvoluce_reverb.m (simulation of room reverberations) File
  • ———————————————————

    Exercise 11 -  Digital fitlering in the frequency-domain II

    - Band filtering in OLA technique using general window.

  • Practical excercise in MATLAB URL
  • cv_ola_general_part1.m (OLA technique with general window) File
  • cv_ola_general_part2.m (freq.-domain band filtering, spectral subtraction) File
  • ———————————————————

    Exercise 12 -  Basics of Multi-Band signal Processing 

    - decimation, interpolation, filter banks

  • Practical excercise in MATLAB URL
  • cv_multiband.m (multiband signal processing, filter banks) File
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    TEST No. 2 -  signals 

    signal_001.mat

    signal_002.mat
    

    signal_003.mat
    

    sigs_004.mat
    

• Assignments
  

  Assignments

  • Spectral subtraction - Delivery of BONUS task Assignment
• References
  

  References

  [1] Oppenheim, A. V., Schafer, F. 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.

  Or any other book devoted to digital signal processing.