Signals and Systems Lab Report – Brain Signal Simulation in MATLAB

If you’re stuck on an open-ended lab task, this signals and system lab report is for you.

Ideally, in an open-ended lab report, you have to choose a task that exhibits your understanding of the subject and learned material so far.

This is what I did, back in my time. It’s a 3D visualization of a simulated brain signal.

It displays the understanding of the following learned commands in MATLAB:

a) Continuous-time signals and their properties

b) Periodic and aperiodic signals

c) Superposition principle

d) Time-domain signal visualization

After the MATLAB code, I’ve explained the learned material in deeper detail too.

Open Ended Signals and Systems Lab Report Task

MATLAB Code

t = linspace(0, 2*pi, 1000); 

frequency = 1; 

amplitude_cos = 1; 

amplitude_sawtooth = 0.5; 

brain_signal = amplitude_cos * cos(2*pi*frequency*t) + amplitude_sawtooth * sawtooth(2*pi*frequency*t);

figure;

plot(t, brain_signal, 'LineWidth', 2);

title('Simulated Brain Signal');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

figure;

subplot(2, 1, 1);

plot(t, amplitude_cos * cos(2*pi*frequency*t), 'LineWidth', 2);

title('Cosine Component');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

subplot(2, 1, 2);

plot(t, amplitude_sawtooth * sawtooth(2*pi*frequency*t), 'LineWidth', 2);

title('Sawtooth Component');

xlabel('Time (s)');

ylabel('Amplitude');

grid on;

Output

Note that when you run the code on MATLAB, you will get two displays/outputs. One of these will be the figure you see above.

The second is attached below. This is because the same code obtains cosine component and sawtooth wave of the simulated brain signal.

Concepts Learned Before the Lab

1. Basic Signal Types

Cosine signal as a periodic, continuous-time deterministic signal.
Sawtooth signal as a non-sinusoidal periodic waveform with a linear rise and sudden drop.
How these two signals differ in shape, frequency content, and harmonic structure.

2. Signal Representation in Time Domain

Using MATLAB to generate and visualize signals over a defined time vector (t = linspace(0, 2*pi, 1000)).
Understanding how frequency, amplitude, and phase affect a signal’s appearance.

3. Signal Superposition (Addition of Signals)

How multiple signals (here, cosine + sawtooth) can be combined to form a composite signal.
The principle of linearity and superposition in signals and systems — a key foundation in system analysis.

4. Periodic Signals and Frequency Components

Recognizing that both cosine and sawtooth are periodic, with the same base frequency but different harmonic content.
The sawtooth wave has higher harmonics, giving the final “brain signal” a richer shape.

5. MATLAB Skills

Creating vectors and functions using MATLAB.
Using functions like cos() and sawtooth() to generate signals.
Plotting multiple figures and subplots to compare components and resultant signals.
Customizing plots with labels, titles, grid, and line width.

6. Signal Interpretation (Application Angle)

Interpreting how real-world signals (like a “simulated brain signal”) can be modeled by combining simple waveforms.
Understanding that real biological signals (EEG, ECG, etc.) are often combinations of simpler periodic and aperiodic signals.

End Note

If you’re looking for more tasks for your signals and systems lab report, browse these:

Good luck!

Biomed Forum