The Introduction of Time-Scales in Reservoir Computing, Applied to Isolated Digits Recognition

Author:

Schrauwen Benjamin,Defour Jeroen,Verstraeten David,Van Campenhout Jan

Publisher

Springer Berlin Heidelberg

Reference8 articles.

1. Omlin, C.W., Giles, C.L.: Constructing deterministic finite-state automata in sparse recurrent neural networks. In: IEEE International Conference on Neural Networks (ICNN’94), Piscataway, NJ, pp. 1732–1737. IEEE Computer Society Press, Los Alamitos (1994)

2. Kilian, J., Siegelmann, H.T.: The dynamic universality of sigmoidal neural networks. Information and Computation 128, 48–56 (1996)

3. Hammer, B., Steil, J.J.: Perspectives on learning with recurrent neural networks. In: Proceedings of ESANN (2002)

4. Maass, W., Natschläger, T., Markram, H.: Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural computation 14(11), 2531–2560 (2002)

5. Jaeger, H.: Short term memory in echo state networks. Technical Report GMD Report 152, German National Research Center for Information Technology (2001)

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