A Compressed Sensing Signal Processing Research

Abstract

The classical Shannon/Nyquist sampling theorem tells us that in order to not lose information when uniformly sampling a signal we must sample at least two times faster than its bandwidth. Nowadays in many applications, because of the restriction of the Nyquist rate, we end up with too many samples and it becomes a great challenge for further transmission and storage. In recent years, an emerging theory of signal acquirement, compressed sensing(CS), is a ground-breaking idea compared with the conventional framework of Nyquist sampling theorem. It considers the sampling in an novel way, and open up a brand new field for signal sampling process. It also reveals a promising future of application. In this paper, we review the background of compressed sensing development. We introduce the framework of CS and the key technique and illustrate some naïve application on image process.