Multiclass Pattern Recognition Extension for the New C-Mantec Constructive Neural Network Algorithm-Reference-Cited by-同舟云学术

Multiclass Pattern Recognition Extension for the New C-Mantec Constructive Neural Network Algorithm

Published:2010-06-03 Issue:4 Volume:2 Page:285-290
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Subirats José L.,Jerez José M.,Gómez Iván,Franco Leonardo

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1007/s12559-010-9051-6.pdf

Reference14 articles.

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2. Lawrence S, Giles CL, Tsoi AC. What size neural network gives optimal generalization ? Convergence properties of backpropagation. In: Technical report UMIACS-TR-96-22 and CS-TR-3617, Institute for Advanced Computer Studies, Univ. of Maryland. 1996.

3. Gómez I, Franco L, Jerez JM. Neural network architecture selection: Can function complexity help? Neural Process Lett. 2009;30:71–87.

4. Franco L, Elizondo D, Jerez JM, editors. Constructive neural networks. Berlin: Springer; 2010.

5. Smieja FJ. Neural network constructive algorithms: trading generalization for learning efficiency? Circuits Syst Signal Process. 1993;12:331–74.

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