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PREDICTIVE CODING WITH NEURAL NETS: APPLICATION TO TEXT COMPRESSION

Jürgen Schmidhuber, Stefan Heil, TUM

In G. Tesauro, D. S. Touretzky and T. K. Leen, eds., Advances in Neural Information Processing Systems 7, NIPS'7, pages 1047-1054. MIT Press, Cambridge MA, 1995.

Abstract:

To compress text files, a neural predictor network $P$ is used to approximate the conditional probability distribution of possible ``next characters'', given $n$ previous characters. $P$'s outputs are fed into standard coding algorithms that generate short codes for characters with high predicted probability and long codes for highly unpredictable characters. Tested on short German newspaper articles, our method outperforms widely used Lempel-Ziv algorithms (used in UNIX functions such as ``compress'' and ``gzip'').





Juergen Schmidhuber 2003-02-25