Statistical mechanics of lossy compression for non-monotonic multilayer perceptrons
A lossy data compression scheme for uniformly biased Boolean messages is investigated via statistical mechanics techniques. The present paper utilize tree-like committee machine (committee tree) and tree-like parity machine (parity tree) whose transfer functions are non-monotonic, completing the stu...
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| creator | Cousseau, F. Mimura, K. Okada, M. |
| description | A lossy data compression scheme for uniformly biased Boolean messages is investigated via statistical mechanics techniques. The present paper utilize tree-like committee machine (committee tree) and tree-like parity machine (parity tree) whose transfer functions are non-monotonic, completing the study of the lossy compression scheme using perceptron-based decoder. 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. |
| doi_str_mv | 10.1109/ISIT.2008.4595038 |
| format | Conference Proceeding |
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| ispartof | 2008 IEEE International Symposium on Information Theory, 2008, p.509-513 |
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| language | eng |
| recordid | cdi_ieee_primary_4595038 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Decoding Equations Mathematical model Multilayer perceptrons Rate-distortion Stability analysis Stability criteria |
| title | Statistical mechanics of lossy compression for non-monotonic multilayer perceptrons |
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