Consider an array of threshold devices, such as neurons or
comparators, where each device receives the same input signal, but
is subject to independent additive noise. When the output from
each device is summed to give an overall output, the system acts
as a noisy Analog to Digital Converter (ADC). Recently, such a
system was analyzed in terms of information theory, and it was
shown that under certain conditions the transmitted information
through the array is maximized for non-zero noise. Such a
phenomenon where noise can be of benefit in a nonlinear system is
termed Stochastic Resonance (SR). The effect in the array of
threshold devices was termed Suprathreshold Stochastic Resonance
(SSR) to distinguish it from conventional forms of SR, in which
usually a signal needs to be subthreshold for the effect to occur.
In this paper we investigate the efficiency of the analog to
digital conversion when the system acts like an array of simple neurons, by analyzing the average distortion incurred and comparing this distortion to that of a conventional flash ADC.