Code [github link]: Real-time video conversion into phototransduction mechanisms. The result is passed into the artificial retina simulator.

The original code was developed to assist with upper-limb prosthesis control:

  • C. Arrow, J.K. Eshraghian, H. Wu, S. Baek, H. Iu and K. Nazarpour, "Prosthesis Control Using Spike-Rate Coding in the Retina Photoreceptor Cells", 2021 IEEE International Symposium on Circuits and Systems, Daegu, South Korea, 2021.


Code [github link]: Retina simulator derived from a discrete neuronal network of retinal cells.

The original code was described in the following papers:

  • J.K. Eshraghian, S. Baek W. Thio, Y. Sandamirskaya, H.H.C. Iu and W. Lu, “A Real-Time Retinomorphic Simulator Using a Conductance-Based Discrete Neuronal Network”, 2020 IEEE Artificial Intelligence Circuits and Systems Conference, Milan, Italy, March 2020, pp. 79-83.[pdf]


Code [github link]: a Python package for performing gradient-based learning with spiking neural networks. Rather than reinventing the wheel, it sits on top of PyTorch and takes advantage of its GPU accelerated tensor computation. Pre-designed spiking neuron models are seamlessly integrated within the PyTorch framework and can be treated as recurrent activation units.



Code [github link]: SPICE netlists of a memristor-CMOS ternary logic family.

The original code is described in the following paper:

  • X. Wang, P. Zhou, J.K. Eshraghian, C.-Y. Lin, H. H. C. Iu, T.-C. Chang, S.-M. Kang, “High-Density Memristor-CMOS Logic Family”, IEEE Transactions on Circuits and Systems I: Regular Papers, October 2020, doi: 10.1109/TCSI.2020.3027693.[pdf]

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©2020 by Jason Eshraghian.