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Bounds on rates of variable-basis and neural-network approximation

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2 Author(s)
V. Kurkova ; Inst. of Comput. Sci., Czechoslovak Acad. of Sci., Prague, Czech Republic ; M. Sanguineti

The 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 n elements of an orthonormal variable basis are derived

Published in:

IEEE Transactions on Information Theory  (Volume:47 ,  Issue: 6 )