An analog-to-information converter for wideband signals using a time encoding machine

The compressive sensing theory enables the analog-to-information conversion of a wideband signal directly by sampling the signal below the Nyquist rate and reconstruct the sampled signal perfectly. We developed a unique implementation of compressive sensing that is based on converting the signal to a time-encoded representation. The time encoding process converts an analog signal that has a continuous voltage range to a binary amplitude signal. In a time encoded signal representation, the important information is captured in the time points - the points where zero-crossing occur. This implementation is shown to be effective for signals sparse in frequency domain.