ProposedThis Lab offers a wide range of hands-on projects for students in the fields of Electrical Engineering and Computer Science. Designed to bridge theory and practice, the projects challenge students to apply their academic knowledge to real-world engineering problems, encouraging innovation, teamwork, and independent thinking:
This project investigates advanced methods in digital signal processing (DSP), with a particular focus on real-time data analysis and noise reduction in modern communication systems. Signal processing plays a critical role in a wide range of technologies, including wireless communication, audio and video transmission, biomedical instrumentation, and industrial monitoring. In today’s increasingly data-driven world, the demand for efficient, accurate, and real-time processing of signals has grown significantly.
The project covers the theoretical foundations of DSP, including discrete-time signals and systems, convolution, Z-transform, and frequency domain analysis using the Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT). Emphasis is placed on digital filtering techniques—such as FIR and IIR filter design—and their implementation in noise suppression and signal enhancement.
To bridge theory with practice, we develop and test signal processing algorithms in simulated and real-time environments using MATLAB and/or Python. Key applications include denoising of audio signals, real-time ECG signal analysis, and filtering of sensor data in IoT communication networks.
The ultimate goal of the project is to design signal processing workflows that are computationally efficient and suitable for real-time execution, thus enabling robust performance in embedded systems and low-latency communication scenarios.
