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This simulation demonstrates how sampling rate affects the reconstruction of a waveform. At the top, the smooth triangular input signal is shown. Below it, three reconstructed signals are displayed using different sampling rates: 1 kHz, 500 Hz, and 250 Hz. The 1 kHz sampling rate produces the closest approximation, with many small steps that follow the original shape accurately. When the sampling rate drops to 500 Hz, the reconstructed waveform becomes more blocky and begins to lose detail, show
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This simulation demonstrates how sampling rate affects the reconstruction of a waveform. At the top, the smooth triangular input signal is shown. Below it, three reconstructed signals are displayed using different sampling rates: 1 kHz, 500 Hz, and 250 Hz. The 1 kHz sampling rate produces the closest approximation, with many small steps that follow the original shape accurately. When the sampling rate drops to 500 Hz, the reconstructed waveform becomes more blocky and begins to lose detail, show
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This simulation demonstrates how sampling rate affects signal reconstruction during ADC–DAC conversion. At the top, the smooth sine wave represents the original analog input. Below it, multiple sampled waveforms show how different sampling frequencies capture the signal with varying accuracy. Higher sampling rates create stair-step outputs that closely follow the original waveform, while lower sampling rates produce coarse, distorted approximations. In the lower schematic, the left blocks act as
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This simulation demonstrates how varying the sampling rate impacts the fidelity of signal reconstruction in digital systems. At the top, a sine wave is sampled and reconstructed using different ADC (Analog-to-Digital Converter) and DAC (Digital-to-Analog Converter) clock rates. As the sampling rate decreases, the reconstructed signal becomes less accurate, showing clear distortion. This highlights the importance of choosing an appropriate sampling rate—typically governed by the Nyquist theorem—t
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