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Next: I. INTRODUCTION

SEQUENTIAL NEURAL TEXT COMPRESSION
IEEE Transactions on Neural Networks, 7(1):142-146, 1996.

Jürgen Schmidhuber
IDSIA
http://www.idsia.ch/~ juergen
- Stefan Heil
Technische Universität München

Abstract:

The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions ``compress'' and ``gzip''). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods.





Juergen Schmidhuber 2003-02-13