Abstract
A representational scheme under which the ranking between represented similarities is isomorphic to the ranking between the corresponding shape similarities can support perfectly correct shape classification because it preserves the clustering of shapes according to the natural kinds prevailing in the external world. This article discusses the computational requirements of representation that preserves similarity ranks and points out the relative straightforwardness of its connectionist implementation.
| Original language | English |
|---|---|
| Pages (from-to) | 701-720 |
| Number of pages | 20 |
| Journal | Neural Computation |
| Volume | 9 |
| Issue number | 4 |
| DOIs | |
| State | Published - 15 May 1997 |
| Externally published | Yes |