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arXiv · 0807.4009

Statistical mechanics of lossy compression for non-monotonic multilayer perceptrons

Florent Cousseau·Kazushi Mimura·Toshiaki Omori·Masato Okada
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Abstract

A lossy data compression scheme for uniformly biased Boolean messages is investigated via statistical mechanics techniques. We utilize tree-like committee machine (committee tree) and tree-like parity machine (parity tree) whose transfer functions are non-monotonic. The scheme performance at the infinite code length limit is analyzed using the replica method. Both committee and parity treelike networks are shown to saturate the Shannon bound. The AT stability of the Replica Symmetric solution is analyzed, and the tuning of the non-monotonic transfer function is also discussed.

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Florent Cousseau, Kazushi Mimura, Toshiaki Omori, Masato Okada. 2008-07-25. Statistical mechanics of lossy compression for non-monotonic multilayer perceptrons. https://doi.org/10.1103/physreve.78.021124

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