Study On Technologies Of Sparse Representation And Compressing Transmission Of Local Time-varying Signal

Local time-varying signal is commonly adopted in the fields such as video surveillance,industrial control,power systems and underwater signal transmission.To reduce the bandwidth and power consumption of the local time-varying signals,and to ensure the efficiency and stability of the transmission meantime has always been the research focus.This thesis proposes an adaptive compression transmission algorithm based on robust principal component analysis,which achieves efficient and reliable signal transmission though sparse representation and compression transmission of the local time-varying signal.The main contents are summarized as follows:(1)This thesis introduces the research status and development tendency of the sparse representation and compression transmission,explains some basic relative theories such as sparse representation,Local time-varying signal,compressed sensing and principal component analysis,analyzes the feasibility of sparse representation and compression transmission of local time-varying signal.(2)Then,the thesis proposes a sparse representation and compression transmission method based on RPCA.The continuous local time-varying signal is divided into two parts: the background model and the foreground model.The background model is relatively stable and can be transmitted from time to time,and the foreground model is a sparse.Simulation results show that the model can achieve compressed transmission efficiently.Lower data reconstruction error is obtained while the compression ratio of the data is effectively reduced.(3)According to the different noise in the time-varying signal,this thesis proposes a sparse representation and compression transmission method based on robust principal component analysis.Through introducing bias priors,I bring priori knowledge into the model,so as to compress data more efficiently,and to tackle the influence brought by different noise levels to the robustness of compression algorithms.Proposed a method of DCS and BRPCA compression transmission algorithm to further reduce the compression ratio and improve transmission efficiency.Simulation results indicate that the method based on BRPCA has better performance in reconstruction error and compression ratio.