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An Ultra-Low-Power Neuromorphic Spiking Neuron Design

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KwantaeKim 2023-10-20 at 16.51.08.png

Description

Integrate-and-Fire (IAF) neurons are widely available in neuromorphic spike-processing applications. Analog LIF neurons are considered a breakthrough to realize fully analog, fully asynchronous spiking neural network implementation for ultra-low-power AI-embedded systems. In this project, you will seek to realize an analog ultra-low-power (thus low energy/spike) LIF neuron, having a very low-frequency spiking rate (e.g., <100Hz). The prerequisite course is Analog integrated circuits. If the design result is promising, the study will be summarized and submitted to IEEE conferences such as ISCAS/BioCAS.

Status: Available

Looking for master or semester thesis students
Supervisor: Kwantae Kim <kimkwa@ethz.ch>

Prerequisites

  • Analog integrated circuits

Character

  • 20% Literature review
  • 20% Theory
  • 60% Circuit Design

Professor

Prof. Taekwang Jang <tjang@ethz.ch>

Reference

[1] S. Kim, S. Kim, S. Um, S. Kim, K. Kim and H. -J. Yoo, "Neuro-CIM: ADC-Less Neuromorphic Computing-in-Memory Processor With Operation Gating/Stopping and Digital–Analog Networks," in IEEE Journal of Solid-State Circuits, vol. 58, no. 10, pp. 2931-2945, Oct. 2023, doi: 10.1109/JSSC.2023.3273238.

[2] A. Rubino, C. Livanelioglu, N. Qiao, M. Payvand and G. Indiveri, "Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 68, no. 1, pp. 45-56, Jan. 2021, doi: 10.1109/TCSI.2020.3035575.

[3] S. Vuppunuthala and V. S. Pasupureddi, "3.6-pJ/Spike, 30-Hz Silicon Neuron Circuit in 0.5-V, 65 nm CMOS for Spiking Neural Networks," in IEEE Transactions on Circuits and Systems II: Express Briefs, doi: 10.1109/TCSII.2023.3324584.

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