This simulation demonstrates the effects of sampling rate on analog signals. The top waveform (purple) represents the original continuous triangular signal, while the other waveforms show sampled versions at different frequencies — 1 kHz (green), 500 Hz (orange), and 250 Hz (red). As the sampling rate decreases, the reconstructed waveform becomes more distorted and loses accuracy, illustrating aliasing and quantization effects. A higher sampling rate captures more signal details, producing a wav
This simulation demonstrates the effects of sampling rate on analo…
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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 reconstr…
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What are capacitive encoders and where are they suitable?
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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
This simulation demonstrates how varying the sampling rate impacts …
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Lecture 22: Sampling and Quantization | Signals and Systems | Electrical Engineering and Computer Science | MIT OpenCourseWare
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