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NeuroCOLT
Technical Report NC-TR-99-037
Noisy
Spiking Neurons with Temporal Coding have more
Computational Power than Sigmoidal Neurons
Wolfgang Maass
Institute for Theoretical Computer Science
Technische Universität Graz
Received:22-MAR-1999
Abstract
We exhibit a novel way of simulating sigmoidal neural nets
by networks of noisy spiking neurons in temporal coding. Furthermore
it is shown that networks of noisy spiking neurons with temporal coding
have a strictly larger computational power than sigmoidal neural nets
with the same number of units.
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