Signaalib

Signaalib is a Python library designed for signal processing and analysis. It provides a collection of tools and functions to handle various types of signals, including time-domain and frequency-domain signals. The library is built on top of NumPy and SciPy, leveraging their efficient numerical operations and mathematical functions.

Signaalib offers a range of features for signal processing, such as filtering, Fourier transforms, and spectral analysis. It includes functions for designing and applying digital filters, such as FIR and IIR filters, to manipulate signals in the time domain. The library also supports windowing techniques to reduce spectral leakage and improve the accuracy of frequency-domain analysis.

In addition to filtering and spectral analysis, Signaalib provides tools for signal generation, such as sine waves, square waves, and random noise. It also includes functions for signal visualization, allowing users to plot signals in both the time and frequency domains.

Signaalib is designed to be user-friendly and easy to integrate into existing Python projects. It is well-documented, with clear examples and tutorials to help users get started with signal processing. The library is open-source and available on GitHub, encouraging community contributions and improvements.

Overall, Signaalib is a valuable resource for engineers, scientists, and researchers working with signals and data. Its comprehensive set of tools and functions makes it a powerful and versatile library for signal processing and analysis.