Method Analysis Of Compressive Sensing Theory

Signal sampling bridge contact between analog sources and digital information. That people demand a huge amount of information caused enormous pressure on signal sampling, transfer and storage. How to relieve this pressure and effectively extract useful information that the signal carries is one of the problems of information processing which require immediately solution. Compressed sensing theory (CS), which appears in recent years, provides an effective solution to alleviate these pressures.Compressed sensing theory obtains the signal, at the same time it compresses the data appropriately. However, the traditional signal acquisition and processing include four parts of sampling, compression, transmission and decompression. The sampling process must follow the Nyquist sampling theorem, and this approach needs large volumes of sampling data. What’s more, the process of compression after sampling. wastes a large number of sensors, time and storage space. Compared to this, compressed sensing theory for the sparse representation of signals, combines data acquisition and data compression into one, which makes them have outstanding advantages in the field of signal processing and broad application prospects. As a result of a late start of compressed sensing theory, we also need to continue to develop many of the issues and direction. One of the main research directions is compressed sensing signal reconstruction algorithm. The reconstruction algorithm is the core of compressed sensing theory, and has very important significance in the verification of the accuracy of the compressed signal reconstruction and the sampling process.The paper first reviews the CS theoretical framework and its key technical issues. Secondly, it highlights the knowledge of sensing matrix theory and several FOCUSS reconstruction algorithm. Furthermore, it compare the results of their reconstruction to several other algorithms. At last, we evaluate the open questions of CS theory, discuss the difficult problems that exist in the study, and finally introduce the applications of CS theory.