VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network

@article{Hsieh2012VLSIIO,
  title={VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network},
  author={Hung-Yi Hsieh and Kea-Tiong Tang},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2012},
  volume={23},
  pages={1065-1073}
}
This paper presents a low-power, neuromorphic spiking neural network (SNN) chip that can be integrated in an electronic nose system to classify odor. The proposed SNN takes advantage of sub-threshold oscillation and onset-latency representation to reduce power consumption and chip area, providing a more distinct output for each odor input. The synaptic weights between the mitral and cortical cells are modified according to an spike-timing-dependent plasticity learning rule. During the… CONTINUE READING
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