**# Signal Processing and Telecommunication Analysis in Python
This repository contains academic-grade Python implementations focused on telecommunication systems, signal processing, and spectral analysis. The toolkit features algorithms for determining channel transmission modes, calculating filter cutoff frequencies, and visualizing signal density using spectrograms.
An algorithmic classifier that evaluates physical channel characteristics (such as attenuation, bandwidth boundaries, and signal-to-noise ratio) to determine the most efficient transmission way and its primary real-world application.
- Supported Modes: Guided media (e.g., Coaxial, Fiber Optics, Twisted Pair) and Unguided media (e.g., Terrestrial Microwave, Satellite, Radio frequency bands).
- Objective: Automatically map raw physical channel specs to their optimal industrial use case (e.g., high-speed data backbone vs. localized broadcasting).
A mathematical module designed to calculate and divide the cutoff frequency boundaries for low-pass, high-pass, and band-pass filters.
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Formula: Utilizes standard RC/RL hardware parameters and mathematical approximations where:
$$f_c = \frac{1}{2\pi RC}$$ - Feature: Automatically segments frequencies into passbands and stopbands, helping identify attenuation thresholds for signals under different transmission mediums.
A visual and mathematical analysis tool that generates a Spectrogram to examine how the frequency content of a transmitted signal changes over time.
- Technique: Applies a windowing function (such as Hann or Hamming) alongside the Fast Fourier Transform (FFT).
- Output: Captures localized noise, signal degradation, and power spectral density across the transmission timeline, which is crucial for analyzing real-time communication channels.
To run the code in this repository, you will need the standard Python engineering stack:
numpy- For high-performance array manipulation and mathematical operations.scipy.signal- For processing the Short-Time Fourier Transform and filter design.matplotlib.pyplot- For rendering the 2D Spectrogram heatmaps.
- Clone the repository: