Quantized Spiking Neuron With AD Conversion Functions

jswon

Quantized Spiking Neuron With AD Conversion Functions

This brief presents a simple artificial spiking neuron
and proposes its application to an A/D converter. Depending on
the initial state, which is an analog input, the neuron can generate
spike trains having various spike position patterns. Based on spike
position modulation, the spike train can be symbolized by a digital
output. As a result, the analog input can be encoded into the digital
output. Adjusting a reconfigurable parameter, the neuron can
realize various encodings such as binary and Gray encodings. This
brief also proposes a simple reconfigurable implementation circuit
and experimentally confirms typical A/D conversion functions.

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