Analog-to-Information
<p>Jun 11, 2015 03:25 PM</p>
<p>
Beginning in 2004, a new mathematical theory called "compressed sensing" (CS) has turned conventional signal processing upside-down. CS has applications outside of signal processing, but this project focuses on just applying it to analog-to-digital converters (ADC). </p>
<p>
Conventional ADC sample analog signals at twice the bandwidth contained in the signal, according to the<a href="http://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem" >Nyquist sampling theorem</a> that is taught in freshman electrical engineering courses. The drawback of this approach is that the bandwidth of a signal may be a poor proxy for how much information is in the signal, and so<b> ADC sample at unnecessarily high rate</b>s. Unfortunately, high-rate sampling is inherently more difficult than low-rate sampling. The approach of compressed sensing is to change how we sample, and the benefit is that it is now possible to <b>sample at the <em >information</em></b><b>-rate</b>, which can lead to sampling at rates that are orders of magnitude slower than the Nyquist rate.</p>