A fusion lossy and lossless data compression method based on signal attributes

With the rapid development of automated terminals, it has greatly contributed to the rapid economic growth. However, the rapid development of terminals has led to a rapid increase in the data that needs to be stored. Storing all the massive terminal data without compression requires a huge amount of storage space, while online transmission consumes a large amount of network bandwidth and puts a lot of pressure on the data transmission lines. In practice, the collected sequence data are not always variable and valuable, and may contain a lot of redundant data, which is detrimental to the analysis efficiency and storage space of the data. Meanwhile, for data with different attributes, the compression methods adopted should be different. To address such issues, this paper proposes a fusion lossy and lossless data compression method based on signal attributes, where the lossy compression algorithm adopts compression perception and the lossless compression algorithm adopts LZW coding. For important data, only the lossless compression method is adopted to prevent the loss of important information; for general data, the fusion lossy and lossless compression method is adopted to improve the compression rate.