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Course pages 2020–21

Digital Signal Processing

Contents

Lecture 1 – 2020-10-08

1  Introduction

2  Discrete sequences

Lecture 2 – 2020-10-13

3  Signal strength

4  Types of discrete systems

5  Convolution

Lecture 3 – 2020-10-15

6  Convolution examples

7  Adding sine waves

8  Complex phasors

Lecture 4 – 2020-10-20

9  Fourier transform

10  Convolution theorem

11  Dirac delta

Lecture 5 – 2020-10-22

12  Fourier transform symmetries

13  Sampling and aliasing

14  Zoneplate aliasing demonstration

15  Discrete time Fourier transform

Lecture 6 – 2020-10-27

16  Nyquist limit and reconstruction filters

17  Interpolation

18  Band-pass sampling

19  Discrete Fourier Transform

Lecture 7 – 2020-10-29

20  Fast Fourier transforms

21  FFT based convolution

22  Deconvolution

Lecture 8 – 2020-11-03

23  Spectral estimation using the DFT

24  Window functions

25  Zero padding the DFT input

26  FIR-filters

Lecture 9 – 2020-11-05

27  IIR-filters

28  The z-transform

29  z-transform of IIR filters

Lecture 10 – 2020-11-10

30  Single-pole filter example

31  More z-transform examples

32  IIR-filter design methods

33  Random processes

Lecture 11 – 2020-11-12

34  Deterministic crosscorrelation sequence

35  Autocorrelation sequence and power density spectrum

36  Filtered random sequences

Lecture 12 – 2020-11-17

37  White noise

38  Spectral estimation of noisy signals

39  IQ downconversion

40  Software-defined radio

Lecture 13 – 2020-11-19

41  Visualizing amplitude-modulated IQ signals

42  Frequency modulation and demodulation

43  Digital communication

Lecture 14 – 2020-11-24

44  Pulse shapes and optimal receive filters

45  Audio-visual-compression overview, entropy coding

Lecture 15 – 2020-11-26

46  Predictive coding

47  Correlation and covariance

48  Karhunen–Loève transform

49  Karhunen–Loève transform examples

Lecture 16 – 2020-12-01

50  Discrete cosine transform

51  Colour coordinates

52  Quantization

53  JPEG photo compression

54  Concluding remarks

55  About the assignments