Bounds on rates of variable-basis and neural-network approximation
نویسندگان
چکیده
Tightness of bounds on rates of approximation by feedforward neural networks is investigated in a more general context of nonlinear approximation by variable-basis functions. Tight bounds on the worst case error in approximation by linear combinations of elements of an orthonormal variable basis are derived.
منابع مشابه
Tight bounds on rates of variable-basis approximation
Tight bounds on the approximation rates of nonlinear approximation by variable-basis functions, which include feedforward neural networks, are investigated. The connections with recent results on neural network approximation are discussed.
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عنوان ژورنال:
- IEEE Trans. Information Theory
دوره 47 شماره
صفحات -
تاریخ انتشار 2001