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A Python-based Jupyter Notebook project for computing and visualizing Fourier series coefficients of periodic functions using the Fast Fourier Transform (FFT) method. Includes examples with sine, sawtooth, and triangle waves, along with interactive visualizations to demonstrate convergence with varying harmonic terms.
A Python-based Jupyter Notebook project for computing and visualizing Fourier series coefficients of periodic functions using the Fast Fourier Transform (FFT) method. Includes examples with sine, sawtooth, and triangle waves, along with interactive visualizations to demonstrate convergence with varying harmonic terms.
Explores Fourier series decomposition of periodic signals using NumPy and Matplotlib, leveraging FFT for efficient coefficient calculation.
FFT-based coefficient computation.
Visualization of true functions vs. Fourier approximations.
Support for common waveforms (sine, sawtooth, triangle).
Parameter customization (period, sample points, harmonic terms).
Preconfigured tests for sine, sawtooth, and triangle waves with dynamic plotting.
Uses Nyquist sampling and np.fft.rfft for real-valued coefficient extraction.
[1] E. Messina, “Fourier Series in Python.” Accessed: May 11, 2025. [Online]. Available: https://computationalmindset.com/en/mathematics/fourier-series-in-python.html
[2] “Discrete Fourier Transform (numpy.fft) — NumPy v2.2 Manual.” Accessed: May 11, 2025. [Online]. Available: https://numpy.org/doc/stable/reference/routines.fft.html
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