On the Computational Power of Recurrent Neural Networks for Structures-Reference-Cited by-同舟云学术

On the Computational Power of Recurrent Neural Networks for Structures

Published:1997-04 Issue:3 Volume:10 Page:395-400
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Sperduti Alessandro

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference20 articles.

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2. Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. Belmont, CA: Wadsworth International Group.

3. Finding structure in time;Elman;Cognitive Science,1990

4. Fahlman, S.E. (1991). The recurrent cascade-correlation architecture. In R.P. Lippmann, J.E. Moody, & D.S. Touretzky (Eds.), Advances in neural information processing systems, 3 (pp. 190–196). San Mateo, CA: Morgan Kaufmann.

5. Fahlman, S.E., & Lebiere, C. (1990), The cascade-correlation learning architecture. In D.S. Touretzky (Ed.), Advances in neural information processing systems, 2 (pp. 524–532). San Mateo, CA: Morgan Kaufmann.

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