Reference no: EM132444890
Digital Signal Processing Practical
Part 1: Generate the following signals with MATLAB
1.1 5 Hz sinusoidal
1.2 25 Hz sinusoidal
1.3 5 Hz + 25 Hz sinusoidal
1.4 Random noise signal in the amplitude interval (0.0 1.0)
1.5 Random noise in 1.4 but with a zero mean
Each signal must contain one thousand (1 000) data-points per second. Generate the signals for a time-span of 2 s but only plot the first 0,5-second of data. (Hand in the plots as well as the computer code)
Part 2: Write a MATLAB program to simulate an Analog to Digital converter. The A/D must have the following specifications:
Full-Range input of ± x Volt
y Bit resolution
z Sampling frequency
Part 3: Use a summation of 5 Hz, 10 Hz and 15 Hz sinusoidal signals to represent an analogue signal. Use 1 000 data points per second. Scale the signal to an amplitude of ±12. To digitise this signal use the model of the A/D converter with the following specifications and plot the input and digitised signal on top of each other for the first 0.2 seconds. (Hand in the plots as well as the computer code).
3.1 ±12 Volt full-range input, 12 Bit resolution, 100 Hz sampling frequency.
3.2 ±12Volt full-range input, 2 Bit resolution, 200 Hz sampling frequency.
Part 4: Use a 15 Hz sinusoidal signal to represent an analogue signal. Use 1 000 data points per second. Scale the signal to an amplitude of ±12. To digitise this signal, use the model of the A/D converter with the following specifications and plot the input and digitised signal on top of each other for the first 0.5 seconds:
±12 Volt full-range input, 12 Bit resolution, 20 Hz sampling frequency. What happened in this digitisation process?
(Hand in the plots as well as the computer (MATLAB) code)
Part 5:
5.1 Write a computer (MATLAB) program to determine the DFT or FFT of a signal
x = {4; 3; 5, 6; 2; 3; 5}.
5.2 Test with the following: DFT: ({1; 0; 0; 1}) = {2,1+j; 0,1-j}
(Hand in the computer (MATLAB) code as well)
Part 6:
6.1 Write a computer (MATLAB) program to determine the inverse DFT or inverse FFT of a signal.
Y1 = {20.0000; -1.1180 + 7.6942j; 1.1180 - 1.8164j; 1.1180 + 1.8164j; -1.1180 - 7.16942j}.
6.2 Test with the following: IDFT ({3;j;0;-j})={1;0;1;1}
Attachment:- Digital Signal Processing Practical.rar