Theory and hardware implementation of an analog-to-Information Converter based on Compressive Sensing

In the practical application, Nyquist-Shannon sampling theorem has brought great challenges to high sampling rate, fast processing speed and hardware equipment. In the context, a new theory called Compressive Sensing (CS) has been proposed, which can break the restriction of the Nyquist theorem for sparse signal. The Analog-to-Information Converter(AIC) makes the CS theory into practical, which can replace the traditional Analog-to-Digital Converter (ADC) to sample the high rate signals at lower rate and solve the bottleneck of Shannon-Nyquist theorem. In this paper, we will analyze the mathematical model and architecture of AIC, Finally we proposed a hardware implementation for AIC.