Abstract
The objective of this paper is to present a simple and effective method for removal of both hidden units and weights. In this paper, we propose two methods, the 'Consuming energy' method and the 'Weights power' method, and compare them with the conventional method. According to our computer simulations using the mirror symmetry problem, the Weights power method has shown the best performance with respect to size reduction (removal of units and weights), generalization performance, and the amount of computation required. For example, the number of hidden units reduced to about 40% of the initial state, and the number of weights reduced to less than a fourth of the initial state. In addition, generalization performance was improved more than 10%.
| Original language | English |
|---|---|
| Pages (from-to) | 207-218 |
| Number of pages | 12 |
| Journal | Neurocomputing |
| Volume | 6 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1994 Apr |
ASJC Scopus subject areas
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence