Welcome to the Digital Signal Processing (DSP) Weekly Tasks Repository! This repository is a collaborative project developed as part of the "Digital Signal Processing" course, aiming to apply and demonstrate key DSP concepts through hands-on coding and problem-solving.
Each week, we tackle a specific task that focuses on a core DSP concept, such as filtering, Fourier transforms, convolution, and more. By implementing these concepts programmatically, we deepen our practical understanding of DSP techniques while enhancing our problem-solving skills.
This repository serves as a collection of these weekly tasks, showcasing our journey of learning and applying DSP principles.
- Python
- NumPy: For numerical computations
- SciPy: For signal processing functions
- Matplotlib: For visualizing signals and results
- Streamlit: For building an interactive GUI
- Shahd Sameh
- Soad Saeed
We extend our heartfelt thanks to our professor and course instructors for their invaluable guidance and for fostering a hands-on learning approach to DSP concepts.