Executed Jupyter notebooks and searchable reports for DSP Labs 1-7: sampling, LTI systems, Fourier analysis, frequency response, FIR, IIR, and audio filtering.
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Updated
Aug 30, 2026 - Jupyter Notebook
Executed Jupyter notebooks and searchable reports for DSP Labs 1-7: sampling, LTI systems, Fourier analysis, frequency response, FIR, IIR, and audio filtering.
This project showcases a Python-based DSP application for visualizing interpolation filters applied to audio signals. Built using tkinter, matplotlib, and scipy, it includes a functional GUI and Jupyter notebook to demonstrate zero-order hold (ZOH), linear, and FIR interpolation techniques. Designed for educational use and signal analysis.
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