Low Resource-Consuming Cyber-physical System Sampling Method using Bernoulli Circulant Matrix

Cyber-physical System (CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing (CS) theory is applied to the sampling compression process of CPS system. The CS theory was used to the sampling compression method of CPS system. The Bernoulli circulant matrix, which is easy to be realized and stored, and its construction algorithm were designed to simplify the realization of CS theory in CPS. It is concluded that for random data set, the compression ratio increases from 14.06 % to 42.18 % and the reconstruction error decreases from 27.65 to 1.28 with increasing repetition times. Note that the sampling time are around tens of microseconds and the reconstruction time are around several milliseconds, which indicates a high real-time performance for CPS. In addition, for image data set, the compression ratios are about 42.90 % which indicates a high compression ratio and huge storage resources saving. More importantly, the sampling time and reconstruction time are only several microseconds and several seconds respectively, which indicates a high real-time performance for CPS.