Bounds for the computational power and learning complexity of analog neural nets.

It is shown that high-order feedforward neural nets of constant depth with piecewise-polynomial activation functions and arbitrary real weights can be simulated for Boolean inputs and outputs by neural nets of a somewhat larger size and depth with Heaviside gates and weights from {-1,0,1}. This prov...

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Τόπος έκδοσης:SIAM journal on computing. 26, 3 (1997).
Κύριος συγγραφέας: Maass, Wolfgang
Μορφή: Άρθρο
Γλώσσα:English
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