Searching for linearly separable subsets using the class of linear separability method

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 2, Issue , 2004, Pages 955-959

  Elizondo, David ^a  

^a DE MONTFORT UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

INPUT VECTORS; LINEAR SEPARABILITY METHOD; POLYNOMIAL TIME; SUBSETS;

ALGORITHMS; NEURAL NETWORKS; POLYNOMIALS; PROBLEM SOLVING; RECURSIVE FUNCTIONS; SET THEORY;

NONLINEAR SYSTEMS;

EID: 10944268750     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1380061     Document Type: Conference Paper

References (8)

1. D. A. Elizondo, "The recursive determinist perceptron (rdp) and topology reduction strategies for neural networks," Ph.D. dissertation, Université Louis Pasteur, Strasbourg, France, January 1997.
2. M. Tajine and D. Elizondo, "New methods for testing linear separability," Neurocomputing, vol. 47, pp. 161-188, 2002.
3. M. Tajine and D. Elizondo, "Enhancing the perceptron neural network by using functional composition," Computer Science Department, Université Louis Pasteur, Strasbourg, France, Tech. Rep. 96-07, 1996.
4. M. Tajine and D. Elizondo, "The recursive deterministic perceptron neural network," Neural Networks, vol. 11, pp. 1571-1588, 1997.
5. F. Rosenblatt, Principles of Neurodynamics. Washington D.C.: Spartan, 1962.
6. S. I. Gallant, "Perceptron-based learning algorithms," IEEE Transactions on Neural Networks, vol. 1, no. 2, pp. 179-191, June 1990.
7. C. Campbell and C. Perez Vicente, "The target switch algorithm: A constructive learning procedure for feed-forward neural networks," Neural Computation, vol. 7, no. 6, pp. 1245-1264, November 1995.
8. M. Tajine, D. Elizondo, E. Fiesler, and J. Korczak, "The class of linear separability method," in The European Symposium on Artificial Neural Networks (ESNN97), 1997.