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25 May 2004Optimal quantization for energy-efficient information transfer in a population of neuron-like devices
Suprathreshold Stochastic Resonance (SSR) is a recently discovered
form of stochastic resonance that occurs in populations of neuron-like devices. A key feature of SSR is that all devices in the population possess identical threshold nonlinearities. It has
previously been shown that information transmission through such a
system is optimized by nonzero internal noise. It is also clear
that it is desirable for the brain to transfer information in an
energy efficient manner. In this paper we discuss the energy efficient maximization of information transmission for the case of
variable thresholds and constraints imposed on the energy available to the system, as well as minimization of energy for the case of a fixed information rate. We aim to demonstrate that under certain conditions, the SSR configuration of all devices having identical thresholds is optimal. The novel feature of this work is that optimization is performed by finding the optimal threshold settings for the population of devices, which is equivalent to solving a noisy optimal quantization problem.
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Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, Derek Abbott, "Optimal quantization for energy-efficient information transfer in a population of neuron-like devices," Proc. SPIE 5471, Noise in Complex Systems and Stochastic Dynamics II, (25 May 2004); https://doi.org/10.1117/12.546934