We introduce a model for analog computation with discrete
time in the presence of analog noise
that is flexible enough to cover the most important concrete
cases, such as noisy analog neural nets and networks of spiking neurons.
This model subsumes the classical ...
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We consider recurrent analog neural nets where the output of each
gate is subject to Gaussian noise, or any other common noise
distribution that is nonzero on a large set.
We show that many regular languages cannot be recognized by
networks of this type, and
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