A model for Fast Analog Computation Based on Unreliable Synapses
W. Maass and T. Natschlaeger
We investigate through theoretical analysis and computer simulations the
consequences of unreliable synapses for fast analog computations in networks
of spiking neurons, with analog variables encoded by the current firing
activities of pools of spiking neurons. Our results suggest that the known
unreliability of synaptic transmission may be viewed as a useful tool for
analog computing, rather than as a ``bug'' in neuronal hardware. We also
investigate computations on time series and Hebbian learning in this context
of space-rate coding.
Reference: W. Maass and T. Natschlaeger.
A model for fast analog computation based on unreliable synapses.
Neural Computation, 12(7):1679-1704, 2000.