Lossless data compression scheme based on neural network and SVM

First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.

basic research in computer science and software engineering at sklcs

The State Key Laboratory of Computer Science (SKLCS) is committed to basic research in computer science and software engineering. The research topics of the laboratory include: concurrency theory, theory and algorithms for real-time systems, formal specifications based on context-free grammars, semantics of programming languages, model checking, automated reasoning, logic programming, software testing, software process improvement, middleware technology, parallel algorithms and parallel software, computer graphics and human-computer interaction. This paper describes these topics in some detail and summarizes some results obtained in recent years.

DECODE: a new method for discovering clusters of different densities in spatial data

National Key Basic Research and Development Program of China [2006CB701305]; State Key Laboratory of Resource and Environment Information System [088RA400SA]; Chinese Academy of Sciences

Comparison of wavelet transform methods - The compression of IR spectral data

In this paper, an introduction of wavelet transform and multi-resolution analysis is presented. We describe three data compression methods based on wavelet transform for spectral information,and by using the multi-resolution analysis, we compressed spectral data by Daubechies's compactly supported orthogonal wavelet and orthogonal cubic B-splines wavelet, Using orthogonal cubic B-splines wavelet and coefficients of sharpening signal are set to zero, only very few large coefficients are stored, and a favourable data compression can be achieved.