A Compressed Sensing Signal Processing Research

In the classical Shannon/Nyquist sampling theorem, information is not lost in uniformly sampling a signal, signal must be sampled at least two times faster than its bandwidth. Because of the restriction of the Nyquist rate, it end up with too many samples in many applications, and it becomes a great challenge for further transmission and storage. In recent years, an emerging theory of signal acquirement is a ground-breaking idea compared with the conventional framework of Nyquist sampling theorem, it is called as compressed sensing (CS). Compressed sensing is considered in the sampling as an novel way, and a brand new field is opened up for signal sampling process. It also reveals a promising future of application. The background of compressed sensing development is reviewed in this study. The framework and the key technique of CS are introduced, and some naïve application is illustrated on image process.