Electronic Resource
Springer
Neural processing letters
2 (1995), S. 5-8
ISSN:
1573-773X
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract An iterative pruning method for second-order recurrent neural networks is presented. Each step consists in eliminating a unit and adjusting the remaining weights so that the network performance does not worsen over the training set. The pruning process involves solving a linear system of equations in the least-squares sense. The algorithm also provides a criterion for choosing the units to be removed, which works well in practice. Initial experimental results demonstrate the effectiveness of the proposed approach over high-order architectures.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02309008
Permalink
| Library |
Location |
Call Number |
Volume/Issue/Year |
Availability |
