New methods for testing linear separability.
Date
2002-08-01
Authors
Advisors
Journal Title
Journal ISSN
ISSN
0925-2312
Volume Title
Publisher
Elsevier
Type
Article
Peer reviewed
Yes
Abstract
Description
This paper introduces latest advances in the subject of linear separability. New methods for testing linear separability are introduced. This is a very important area of work which can help simplify the topology of a neural network by using a single layer perceptron when the problem at hand is linearly separable. The research presented in this paper has allowed researchers to enhance the performance of the RDP neural network.
It appears in one of the leading journals of Neural Networks.
Keywords
RAE 2008, UoA 23 Computer Science and Informatics, linear separability, convex hull, perceptron, class of separability
Citation
Tajine, M., and Elizondo, D. (2002) New methods for testing linear separability. Neurocomputing, 47(1-4), pp. 161-188.