Basics

1. Basics of Octave/ MATLAB / Python (Installation) and basics of plotting data.
2. Create a Sinusoidal Signal y(n) and plot the signal.
3. Create 3 Sinusoidal signal y1, y2, y3. then combine them and plot it.
4. Plot the basic signals like unit impulse, unit samples, unit step, exponential, unit ramp (discussed in classes) etc.

• Sampling of a Signal... take a signal then sample using a sampling rate.
• Sampling Theorem Experiment.

6. Determination of Power Spectrum of a given signal.

Core

• Implement some basic systems like Adder, Multiplier, Delay, Advanced ... etc.
• Implementing a system from a system input/output equation (i.e. y(n) = .25 y(n-1) + 1.25 x(n-1) + .25 x(n))

• Implement Moving average filter, Median Filter, Accumulator etc.
• Noise removal: Add noise and then remove.

9. Representing a signal using unit impulse signal.
10. Linear Convolution using Equation
11. DFT/IDFT -> Composite Sinusoidal Signal to see the frequencies
12. Program to find the DFT/IDFT
13. Circular convolution program.

• Linear Convolution by FFT, IFFT [DFT, IDFT]
• Circular convolution by FFT, IFFT [DFT, IDFT]

15. Read a .wav, img file and plot them, play / open them. Then apply DFT and plot.
16. Program for Computing auto correlation and cross correlation.

Filter

17. Implement (design) an FIR Filter → Low Pass
18. Implement (design) an FIR Filter → High Pass
19. Implement (design) an FIR Filter → Band Pass
20. Implement (design) an IIR Filter → Low Pass
21. Implement (design) an IIR Filter → High Pass

Some Practical Applications:

22. Read a .wav file -> mfcc
23. Read an img file -> resize, reshape, flat ( numpy , openCV )
24. image-> grayscale, resize ... other basic operations (OpenCV)
25. Basic Image Processing Methods
26. Speech Processing -> Filter, Convolution etc.
27. Data Compression (text and image)