Exact Classification with Two-Layer Neural Nets
| Autor: | G. J. Gibson |
|---|---|
| Rok vydání: | 1996 |
| Předmět: |
Discrete mathematics
Artificial neural network Computer Networks and Communications Applied Mathematics Theoretical Computer Science Combinatorics Polyhedron Computational Theory and Mathematics Hyperplane Bounding overwatch Bounded function Line (geometry) Point (geometry) General position Mathematics |
| Zdroj: | Journal of Computer and System Sciences. 52:349-356 |
| ISSN: | 0022-0000 |
| DOI: | 10.1006/jcss.1996.0026 |
| Popis: | This paper considers the classification properties of two-layer networks of McCulloch–Pitts units from a theoretical point of view. In particular we consider their ability to realise exactly, as opposed to approximate, bounded decision regions in R2. The main result shows that a two-layer network can realise exactly any finite union of bounded polyhedra in R2whose bounding lines lie in general position, except for some well-characterised exceptions. The exceptions are those unions whose boundaries contain a line which is “inconsistent,” as described in the text. Some of the results are valid for Rn,n⩾2, and the problem of generalising the main result to higher-dimensional situations is discussed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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