Reservoir Size, Spectral Radius and Connectivity in Static Classification Problems

Author:

Alexandre Luís A.,Embrechts Mark J.

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Jaeger, H.: ‘The echo state’ approach to analysing and training recurrent neural networks. Technical Report GMD Report 148, Fraunhofer Institute for Autonomous Intelligent Systems (2001)

2. Maas, 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)

3. Verstraeten, D., Schrauwen, B., D’Haene, M., Stroobandt, D.: An experimental unification of reservoir computing methods. Neural Networks 20, 391–403 (2007)

4. Embrechts, M., Alexandre, L., Linton, J.: Reservoir computing for static pattern recognition. In: 17th European Symposium on Artificial Neural Networks – ESANN 2009, Bruges, Belgium (2009)

5. Alexandre, L., Embrechts, M., Linton, J.: Benchmarking reservoir computing on time-independent classification tasks. In: International Joint Conference on Neural Networks – IJCNN 2009, Atlanta, Georgia, USA, pp. 89–93 (2009)

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