Discrimination of Phase-Coded Spike Trains by Silicon Neurons with Artificial Dendritic Trees
Artificial neurons with dendritic trees, modeled in VLSI, were used to evaluate large numbers of different patterns of synaptic connections onto dendrites. Random search yielded connections that produced well-differentiated responses to input spike patterns that differed only in phasing. Feedforward networks of up to 3 layers exhibited increasing variability that can be exploited for discrimination purposes.
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