State prediction: a constructive method to program recurrent neural networks

Reinhart F, Steil JJ (2011)
In: Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science, 6791. Berlin, Heidelberg: Springer: 159-166.

Conference Paper | Published | English

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Abstract
We introduce a novel technique to program desired state sequences into recurrent neural networks in one shot. The basic methodology and its scalability to large and input-driven networks is demonstrated by shaping attractor landscapes, transient dynamics and programming limit cycles. The approach unifies programming of transient and attractor dynamics in a generic framework.
Publishing Year
Conference
International Conference on Artificial Neural Networks ; 21
Location
Espoo, Finland
Conference Date
2011-06-14 – 2011-06-17
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Reinhart F, Steil JJ. State prediction: a constructive method to program recurrent neural networks. In: Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science. Vol 6791. Berlin, Heidelberg: Springer; 2011: 159-166.
Reinhart, F., & Steil, J. J. (2011). State prediction: a constructive method to program recurrent neural networks. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I, 6791, 159-166.
Reinhart, F., and Steil, J. J. (2011). “State prediction: a constructive method to program recurrent neural networks” in Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I Lecture Notes in Computer Science, vol. 6791, (Berlin, Heidelberg: Springer), 159-166.
Reinhart, F., & Steil, J.J., 2011. State prediction: a constructive method to program recurrent neural networks. In Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science. no.6791 Berlin, Heidelberg: Springer, pp. 159-166.
F. Reinhart and J.J. Steil, “State prediction: a constructive method to program recurrent neural networks”, Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I, Lecture Notes in Computer Science, vol. 6791, Berlin, Heidelberg: Springer, 2011, pp.159-166.
Reinhart, F., Steil, J.J.: State prediction: a constructive method to program recurrent neural networks. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science. 6791, p. 159-166. Springer, Berlin, Heidelberg (2011).
Reinhart, Felix, and Steil, Jochen J. “State prediction: a constructive method to program recurrent neural networks”. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Berlin, Heidelberg: Springer, 2011.Vol. 6791. Lecture Notes in Computer Science. 159-166.
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