Abstract
Adaptive resonance theory (ART) has been used to develop neural network architectures in order to self-organize pattern recognition codes stably in real-time in response to random input sequences of patterns. A brief background of the motivations and design considerations underlying the development of adaptive resonance networks, an outline of their basic operation, a new idea for improving the model, and some experimental results are discussed in this article.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 26-36 |
| Number of pages | 11 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 1382 |
| State | Published - 1991 |
| Event | Intelligent Robots and Computer Vision IX: Neural, Biological, and 3-D Methods - Boston, MA, USA Duration: Nov 7 1990 → Nov 9 1990 |
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering