학술논문

On design and evaluation of tapped-delay neural network architectures
Document Type
Conference
Source
IEEE International Conference on Neural Networks Neural Networks, 1993., IEEE International Conference on. :46-51 vol.1 1993
Subject
Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Neural networks
Biological neural networks
Chaos
Statistical analysis
Optimization methods
History
Feeds
Feedforward neural networks
Prediction algorithms
Noise generators
Language
Abstract
Pruning and evaluation of tapped-delay neural networks for the sunspot benchmark series are addressed. It is shown that the generalization ability of the networks can be improved by pruning using the optimal brain damage method of Le Cun, Denker and Solla. A stop criterion for the pruning algorithm is formulated using a modified version of Akaike's final prediction error estimate. With the proposed stop criterion, the pruning scheme is shown to produce successful architectures with a high yield.ETX