Author:
Cabessa Jérémie,Finkel Olivier
Publisher
Springer Berlin Heidelberg
Reference23 articles.
1. Apt, K.R.:
$$\omega $$
-models in analytical hierarchy. Bulletin de l’académie polonaise des sciences XX(11), 901–904 (1972)
2. Balcázar, J.L., Gavaldà, R., Siegelmann, H.T.: Computational power of neural networks: a characterization in terms of Kolmogorov complexity. IEEE Trans. Inf. Theory 43(4), 1175–1183 (1997)
3. Cabessa, J., Duparc, J.: Expressive power of nondeterministic recurrent neural networks in terms of their attractor dynamics. IJUC 12(1), 25–50 (2016)
4. Cabessa, J., Siegelmann, H.T.: Evolving recurrent neural networks are super-Turing. In: Proceedings of IJCNN 2011, pp. 3200–3206. IEEE (2011)
5. Cabessa, J., Siegelmann, H.T.: The computational power of interactive recurrent neural networks. Neural Comput. 24(4), 996–1019 (2012)
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献