2 / 5 / 2025

Task - 01: Engineer’s Swiss Army Knife

Steps Followed:

1. Created an account at https://matlab.mathworks.com.
2. Accessed the MATLAB Onramp course under the "Learn" tab.
3. Completed all interactive modules, including:
   • MATLAB Basics
   • Variables and Commands
   • Visualizations
   • Programming Constructs
   • Functions
4. Successfully completed the course and obtained the certification.

Certification:

Task - 02: Cut, Pass, Repeat

Objective:
To learn about Band Pass Filters.

I made a band pass filter which filters out frequencies outside the 4 kHz to 10 kHz range and allows only the desired frequency band to pass through. I learned how to design and simulate second-order band pass filters using operational amplifiers, how to calculate key parameters like center frequency, bandwidth, and quality factor, and how to achieve a specific gain. This helped me understand frequency-domain signal processing and practical filter design in LTSpice.

Parameters:

1. Fm = 6.32 kHz
2. Bandwidth (BW) = Fhigh - Flow = 6 kHz
3. Quality Factor (Q) = Fm / BW = 1.053

Component Specs:

• Capacitors (C): 0.01 μF (both)
• Resistors (R): 10 kΩ (used throughout)
• Gain: Designed to achieve ~1.5× amplification

Task - 03: SPICEy Code

Circuit Design:

1. MOS Inverter: CMOS inverter using complementary NMOS and PMOS transistors.
2. AND Gate: CMOS logic design using series NMOS and parallel PMOS.
3. OR Gate: CMOS logic using parallel NMOS and series PMOS.

Inverter Output:

AND Gate Output:

OR Gate Output:

Outcome:

Successfully wrote and simulated SPICE code for basic MOS Inverter, AND, and OR gates using LTSpice. The simulation results matched expected logic behavior, helping me understand CMOS gate design and how to implement digital logic at the transistor level using raw SPICE syntax.

Task - 08: Linear Convolution

I learned the fundamentals of Digital Signal Processing, including signals, systems, the Z-Transform, and the Fourier Transform. I understood how linear convolution is used to determine the output of an LTI system. In MATLAB, I implemented and visualized the linear convolution of two 4-sample discrete-time signals using the conv() function, which helped me understand how input signals interact with system responses in the time domain.