Journal of Xidian University ›› 2016, Vol. 43 ›› Issue (4): 178-183.doi: 10.3969/j.issn.1001-2400.2016.04.031

• Article • Previous Articles     Next Articles

Spectrum analysis compression algorithm of measure report data

CHENG Fei;LIU Kai;DING Wenwen;SHI Huan;ZHANG Baijian   

  1. (School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China)
  • Received:2015-10-19 Online:2016-08-20 Published:2016-10-12

Abstract:

To solve to the problem that with the increment of the number of mobile users, the network bandwidth cannot meet the mass transfer of the measure report. This paper defines the conception of the spectrum of the measure report and proposes a spectrum analysis compression algorithm for the measure report. The algorithm utilizes two step sorting in order to reduce the distance between similar contents according to the analysis of the spectrum of measure report data. Furthermore, this algorithm employs several context models, which are regarded as the input nodes of the neural network. The prediction probability is calculated by the linear combination of the probability of each context model, and the weight in each link is tuned by the next bit in order to increase the possibility of matching. Experimental results reveal that the algorithm not only decreases the compression consuming time, but also ascends the compression ratio with the increment of the size of compression data. Compared with other competitors, this algorithm can effectively increase the compression ratio of the measure report to gain a better transfer time.

Key words: measure report, data compression, spectrum analysis, neural network


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