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How to get the most out of the exercises

  • I try to upload next week's exercise materials after each exercise
    • Take some time during the week to look at the problem statement
    • try to solve it yourself
    • If you run into problems, ask me – email or in person – or start reading suggested literature
  • After each exercise, you are going to get the solutions for the theory part
    • You do not need to copy everything from the whiteboard
    • I am not going to wait until everyone has copied everything
  • Thus, during the exercise: Think, listen, talk with me, ask questions
    • Try to only write down key points, tricks, shortcuts, etc...
  • redo the calculations yourself when you have the solutions

Python Crashcourse

Support Notebooks

Exercise Materials

  1. (2019-04-18) Continuous and Discrete Time Fourier Transform
    Solution - Notebook (as html)
  2. (2019-04-18) Sampling and Reconstruction
  3. (optional homework) Energy and Parseval Theorem
  4. (2019-04-25) DFT and Computational Effort Notebook (as html preview)
    (Update 2019-04-25: Fixed errors in notebook)
    Solution - Notebook as html
  5. (2019-05-02) Overlap-Save & Partioned FilteringNotebook (as html preview)
  6. (2019-05-09) Window Functions & Leakage EffectNotebook (as html preview)
  7. (2019-05-22) Periodogram and ACF EstimationNotebook (as html preview)
    Solution - Notebook as html
    (Note: Subtask 7.5 and 7.9 belong to Exercise 8)
  8. (2019-05-22) Linear Estimator for Auto-regressive Processes
    (Note: Subtask 7.5 and 7.9 are discussed afterwards)
  9. (2019-06-27) Wiener Filter for Noise SuppressionNotebook (as html preview)
    (Note: This is going to be a double exercise - first half theory, second half coding)
  10. (dropped)
  11. (2019-07-11) LMS (Adaptive Filters) - Matlab programs as zip archive

Die Universität der Informationsgesellschaft