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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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Jstewart083/Interpolation-filtering-python

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Audio Interpolation Filter Tool

This Python application visualizes the effects of basic digital filtering techniques — including zero-order hold (ZOH), linear interpolation, and FIR filtering — as applied to audio signals. It offers both an interactive GUI and an educational Jupyter notebook to explore how different interpolation methods reshape waveforms after upsampling.


Features

  • Load and visualize .wav audio files
  • Perform upsampling using a selectable factor (L)
  • Apply interpolation methods:
    • Zero-Order Hold (ZOH)
    • Linear Interpolation
    • FIR Filtering with gain compensation
  • Visualize waveform output from each method
  • Modular signal processing logic (filters.py)
  • Two usage modes:
    • Graphical Interface (GUI)
    • Educational Jupyter Notebook

Getting Started

Installation

Clone the repository and install dependencies:

git clone https://github.com/jstewart083/interpolation-filtering-python.git
cd interpolation-filtering-python
pip install -r requirements.txt

About

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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