MEMRISTIVE IMPLEMENTATION OF SPIKING NEURONS AND SYNAPSES
DOI:
https://doi.org/10.24867/16BE11VincanKeywords:
neuromorphic computing, spiking neuron, synapse, STDP learning rule, memristorAbstract
In this paper, software implementations of the memristive Morris-Lecar model of the spiking neuron and the memristive Zamarreno model of the synapse have been developed. Matlab and Simulink models of memristors have been used for the simulation of calcium and potassium channels of the Morris-Lecar neuron model. It has been shown, how the STDP learning rule can be implemented on the memristive Zamarreno model of the synapse.
References
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[15] L. Chua, V. Sbitnev and H. Kim, “Hodkin-Huxley Axon Is Made Of Memristors,” International Journal of Bifurcation and Chaos, vol. 22, no. 3, pp. 123011--, 2012.
[16] S. Kvatinsky, M. Ramadan, E. G. Friedman and A. Kolodny, “VTEAM - A General Model for Voltage Controlled Memristors,” IEEE Transactions on Circuits and Systems, vol. 62, no. 8, 2015.
[2] L. Chua, “Memristor - The Missing Circuit Element,” IEEE Transactions on Circuit Theory, vol. 18, 5 September 1971.
[3] D. B. Strukov, G. S. Snider, D. R. Stewart and R. S. Williams, “The missing memristor found,” Nature, vol. 453, pp. 80-83, 1 May 2008.
[4] O. Krestinskaya, A. P. James and L. O. Chua, “Neuromemristive circuits for edge computing: A review,” IEEE transactions on neural networks and learning systems, vol. 31, no. 1, pp. 4-23, 2019.
[5] M. Zidan, J. Strachan and W. Lu, “The future of electronics based on memristive systems,” Nature Electronics, vol. 1, p. 22–29, 2018.
[6] C. Zamarreño-Ramos, L. A. Camuñas-Mesa, J. A. Pérez-Carrasco, T. Masquelier, T. Serrano-Gotarredona and B. Linares-Barranco, “On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex,” Frontiers in Neuroscience, vol. 5, 17 March 2011.
[7] C. Morris and H. Lecar, “Voltage oscillations in the barnacle giant muscle fiber,” Biophysical Journal, vol. 35, no. 1, pp. 193-213, 1 July 1982.
[8] L. Chua, “Everything You Wish To Know About Memristors But Are Afraid To Ask,” Radioengineering, vol. 24, no. 2, pp. 319-368, 2 June 2015.
[9] J. Sjöström and W. Gerstner, “Spike-timing dependent plasticity,” Scholarpedia, vol. 5, 2010.
[10] M. P. Sah, H. Kim, A. Eroglu and L. Chua, “Memristive Model of the Barnacle Giant Muscle Fibers,” International Journal of Bifurcation and Chaos, vol. 26, no. 1, p. 1630001, 2016.
[11] W. Gerstner and W. M. Kistler, Spiking Neuron Models, Cambridge University Press, 2002.
[12] M. M. Adnan, S. Sayyaparaju, G. S. Rose, C. D. Schuman, B. W. Ku and S. K. Lim, “A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems,” in 2018 31st IEEE International System-on-Chip Conference (SOCC), 2018 .
[13] M. P. Sah, H. Kim and L. O. Chua, “Brains Are Made of Memristors,” IEEE Circuits and Systems Magazine, vol. 14, no. 1, pp. 12-36, 2014.
[14] A. L. Hodgkin and A. F. Huxley, “A quantitative description of membrane current and its application to conduction and excitation in nerve,” The Journal of physiology, vol. 117, no. 4, pp. 500-544, 28 August 1952.
[15] L. Chua, V. Sbitnev and H. Kim, “Hodkin-Huxley Axon Is Made Of Memristors,” International Journal of Bifurcation and Chaos, vol. 22, no. 3, pp. 123011--, 2012.
[16] S. Kvatinsky, M. Ramadan, E. G. Friedman and A. Kolodny, “VTEAM - A General Model for Voltage Controlled Memristors,” IEEE Transactions on Circuits and Systems, vol. 62, no. 8, 2015.
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Published
2022-01-29
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Electrotechnical and Computer Engineering
