Sub-Nyquist sampling of high-speed repetitive waveforms using compressed sensing

This study presents a sub-Nyquist sampling model using compressed sensing (CS) as a new signal processing framework to acquire and reconstruct sparse signals. High-speed periodic signals were sampled using low frequency sampling circuit and reconstructed via CS recovery algorithm, resulting in a high equivalent sampling frequency. This prototype system is able to capture repetitive waveforms at an equivalent sampling rate of 2.5 GHz while sampling at no more than 50 MHz physically.

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