Using Fourier-neural recurrent networks to fit sequential input/output data
نویسندگان
چکیده
This paper suggests the use of Fourier-type activation functions in fully recurrent neural networks. The main theoretical advantage is that, in principle, the problem of recovering internal coefficients from input/output data is solvable in closed form.
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عنوان ژورنال:
- Neurocomputing
دوره 15 شماره
صفحات -
تاریخ انتشار 1997