A Compression Algorithm for Multi-streams Based on GEP

This paper applied the Methods which based on GEP in compress multi-streams. The contributions of this paper include: 1) giving an introduction to data function finding based on GEP(DFF-GEP), defining the main conception of Multi-Streams, and revealing the map relation in it; 2) putting forward the Compression Algorithm for Multi-Streams according to map relation lied in data between data streams; and 3)providing an experience with the real data and find that (3.1) the compression ratio of the new methods is 120¿150 times as the traditional wavelets method, and 35¿70 times as the wavelets and coincidence method; (3.2) the relative error of the new method is about 3¿, yet maximum relative error is 0.01 by using the traditional relative error standard, the precision is improved from 7% to 15% as compared with the traditional method.