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- W2117788424 abstract "Inspired by the universal laws governing different kinds of complex networks, we propose a scale-free highly-clustered echo state network (SHESN). Different from echo state network (ESN), the state reservoir of the SHESN is generated by natural growth rules and eventually forms a complex network with small-world, scale-free properties, and hierarchically distributed structure. We implemented a large-scale SHESN with 3,000 internal neurons and applied it to modeling the pH-neutralization process. Simulation results showed the superior performance of SHESN. Furthermore, we analyzed the natural characteristics of the SHESN and discussed our growth rules and the new state reservoir from a brain functional network perspective." @default.
- W2117788424 created "2016-06-24" @default.
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- W2117788424 date "2006-01-01" @default.
- W2117788424 modified "2023-09-27" @default.
- W2117788424 title "Complex Systems Modeling Using Scale-Free Highly-Clustered Echo State Network" @default.
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- W2117788424 doi "https://doi.org/10.1109/ijcnn.2006.247295" @default.
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