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- W2386452714 abstract "Functional network is a recently introduced extension of neural networks. Unlike neural networks, it deals with general functional models instead of sigmoid-like ones. And in these networks there are no weights associated with the links connecting neurons. In this paper, we propose a functional network method for the identification of nonlinear systems. And the learning of parameters of the functional networks is carried out by the gradient descent algorithm. The simulation results demonstrate that the identification method presented in the paper has rapid convergence speed and powerful performance." @default.
- W2386452714 created "2016-06-24" @default.
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- W2386452714 date "2001-01-01" @default.
- W2386452714 modified "2023-09-23" @default.
- W2386452714 title "Functional Network Method for the Identification of Nonlinear Systems" @default.
- W2386452714 hasPublicationYear "2001" @default.
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