Abstract
Aim to solve the problems of structure design and parameters selection about conventional ESN, a small world property ESN (SWESN) is proposed in this paper. Neuron space growth algorithm is adopted to generate a physical network with small world topology on 2-D plane firstly, and then the nodes and the connections of the physical network are mapped into the neurons in reservoir of SWESN, Thus the dynamic neuron reservoir (DNR) in SWESN has small world characteristic. In addition, different typical neurons are adopted in the reservoir. The simulation experiments confirms that the SWESN generated by this method could create more abundant dynamic behavior than conventional ESN, and SWESN exceeds conventional ESN both at robustness and at anti-disturbance ability.
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Bo, Y., Qiao, J., Wang, S. (2011). Research on Design Method of Small World Property ESN. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21105-8_7
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DOI: https://doi.org/10.1007/978-3-642-21105-8_7
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