Simulation showing how a signal can be reconstructed based on the sampling frequency
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Updated
Jun 20, 2025 - Python
Simulation showing how a signal can be reconstructed based on the sampling frequency
An illustrator for the signal recovery that shows the importance and validation of the Nyquist rate.
Real-time ultrasonic spectrum display using your microphone. Captures audio via PortAudio (sounddevice), computes an FFT, and plots only the ultrasonic band (>20 kHz). Includes a control panel to adjust device, sample rate, block size, min frequency, and FFT size while running.
A python script that implements an automatic speech recognision system.
Interactive DSP visualization platform demonstrating sampling, aliasing, Nyquist theory, FFT analysis, and anti-aliasing filters through real-time simulations, audio processing, and dynamic visualizations.
Projekt ma na celu rozwój narzędzi do analizy stabilności systemów dynamicznych przy użyciu kryteriów Nyquista i Michajłowa.
Tested Python toolkit for Nyquist analysis, aliasing simulation, ADC filtering, and engineering design recommendations.
A modern, high-performance Python control systems library built on NumPy, SciPy, and Plotly.
Academic MATLAB/Simulink portfolio covering nonlinear systems, rotary-arm control, active suspension, magnetic levitation and two-tank process control.
A Signal Sampling and Reconstruction Studio for analyzing signal sampling interactively. Users can load or compose a signal, sample it with a chosen sampling frequency, and visualize it's reconstruction using Whittaker-Shannon interpolation, Cubic Spline, or a Fourier low-pass filter with linear interpolation.
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