Abstract
Within the context of a particular statistical discrimination task, we make a quantitative comparison between the performance of a feed-forward neural network and the information-theoretic optimal performance. We also address the ability of such networks to generalize and the effect of network architecture on performance.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 141-156 |
| Number of pages | 16 |
| Journal | Journal of Statistical Physics |
| Volume | 57 |
| Issue number | 1-2 |
| DOIs | |
| State | Published - Oct 1989 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Statistical and Nonlinear Physics
- Mathematical Physics
Keywords
- Neural network
- information theory
- optimal performance
- statistical discrimination
- visual system
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