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Handbook of Memristor Networks pp 555–570Cite as

Associative Enhancement and Its Application in Memristor Based Neuromorphic Devices

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Abstract

Binary state resistance switching memristors and multistate or continuum resistance memristors have begun to diverge in their application. The former application in non-volatile logic memory and the later with more focus on neuromorphic computation. The properties of continuum resistance memristors as neuromorphic hardware are presented in this paper. Concepts such as polymorphism, voltage flux equivalence and non voltage based memristive flux are discussed. Emergent functionalities observed in neuromorphic hardware such as associative enhancement of current/charge generation, spike time dependent plasticity (STDP) and associative memory between voltage and light pulse stimuli are expanded upon. Finally various applications that this hardware may enable such as machine learning and adaptive programs for brain-like functionality are discussed.

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References

  1. Markram, H., Gerstner, W., Sjöström, P.J.: Spike-timing-dependent plasticity: a comprehensive overview. Front. Synaptic Neurosci. 4, 2 (2012)

    Google Scholar 

  2. Linares-Barranco, B., Serrano-Gotarredona, T., Camuñas-Mesa, L.A., Perez-Carrasco, J.A., Zamarreño-Ramos, C., Masquelier, T.: On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex. Front. Neurosci. 5, 26 (2011)

    Google Scholar 

  3. Lodish, H., Berk, A., Kaiser, C.A., Krieger, M., Scott, M.P., Bretscher, A., Ploegh, H., Matsudaira, P.: Mol. Cell Biol., 7th edn. Freeman, W. H (2012)

    Google Scholar 

  4. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436–444 (2015)

    Article  Google Scholar 

  5. Huang, G., Huang, G.-B., Song, S., You, K.: Trends in extreme learning machines: a review. Neural Netw. 61, 32–48 (2015)

    Article  Google Scholar 

  6. Djurfeldt, M., Lundqvist, M., Johansson, C., Rehn, M., Ekeberg, O., Lansner, A.: Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer. IBM J. Res. Dev. 52, 31–41 (2008)

    Article  Google Scholar 

  7. Merolla, P.A., Arthur, J.V., Alvarez-Icaza, R., Cassidy, A.S., Sawada, J., Akopyan, F., Jackson, B.L., Imam, N., Guo, C., Nakamura, Y., Brezzo, B., Vo, I., Esser, S.K., Appuswamy, R., Taba, B., Amir, A., Flickner, M.D., Risk, W.P., Manohar, R., Modha, D.S.: A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345, 668–673 (2014)

    Article  Google Scholar 

  8. Chua, L.: Memristor-the missing circuit element. IEEE Trans. Circ. Theory 18, 507–519 (1971)

    Article  Google Scholar 

  9. Strukov, D.B., Snider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453, 80–83 (2008)

    Article  Google Scholar 

  10. Pershin, Y.V., Castelano, L.K., Hartmann, F., Lopez-Richard, V., Ventra, M.D.: A memristive pascaline. IEEE Trans. Circuits Syst. II Express Briefs 63, 558–562 (2016)

    Article  Google Scholar 

  11. Traversa, F.L., Ventra, M.D.: Universal memcomputing machines. IEEE Trans. Neural Netw. Learn. Syst. 26, 2702–2715 (2015)

    Article  MathSciNet  Google Scholar 

  12. Pershin, Y.V., Shevchenko, S.N.: Computing with volatile memristors: an application of non-pinched hysteresis. Nanotechnology 28, 075204 (2017)

    Article  Google Scholar 

  13. Ohno, T., Hasegawa, T., Tsuruoka, T., Terabe, K., Gimzewski, J.K., Aono, M.: Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. Nat. Mater. 10, 591–595 (2011)

    Article  Google Scholar 

  14. van de Burgt, Y., Lubberman, E., Fuller, E.J., Keene, S.T., Faria, G.C., Agarwal, S., Marinella, M.J., Alec Talin, A., Salleo, A.: A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. Nat. Mater. 16, 414–418 (2017)

    Article  Google Scholar 

  15. Caponi, S., Mattana, S., Ricci, M., Sagini, K., Juarez-Hernandez, L.J., Jimenez-Garduño, A.M., Cornella, N., Pasquardini, L., Urbanelli, L., Sassi, P., Morresi, A., Emiliani, C., Fioretto, D., Serra, M.D., Pederzolli, C., Iannotta, S., Macchi, P., Musio, C.: A multidisciplinary approach to study the functional properties of neuron-like cell models constituting a living bio-hybrid system: SH-SY5Y cells adhering to PANI substrate. AIP Adv. 6, 111303 (2016)

    Article  Google Scholar 

  16. Gkoupidenis, P., Schaefer, N., Garlan, B., Malliaras, G.G.: Neuromorphic functions in PEDOT: PSS organic electrochemical transistors. Adv. Mater. 27, 7176–7180 (2015)

    Article  Google Scholar 

  17. O’Kelly, C.J., Abunahla, H.N.M., Abi Jaoude, M., Homouz, D., Mohammad, B.: Subthreshold continuum conductance change in NbO Pt memristor interfaces. J. Phys. Chem. C 120, 18971–18976 (2016)

    Article  Google Scholar 

  18. Chua, L.: Resistance switching memories are memristors. Appl. Phys. A 102, 765–783 (2011)

    Article  Google Scholar 

  19. Pickett, M.D., Medeiros-Ribeiro, G., Williams, R.S.: A scalable neuristor built with Mott memristors. Nat. Mater. 12, 114–117 (2013)

    Article  Google Scholar 

  20. Chiolerio, A., Chiappalone, M., Ariano, P., Bocchini, S.: Coupling resistive switching devices with neurons: state of the art and perspectives. Front. Neurosc. 11 (2017)

    Google Scholar 

  21. Sze, S.M., Ng, K.K.: Physics of semiconductor Devices. John wiley & sons (2006)

    Google Scholar 

  22. O’Kelly, C.J., Fairfield, J.A., McCloskey, D., Manning, H.G., Donegan, J.F., Boland, J.J.: Associative enhancement of time correlated response to heterogeneous stimuli in a neuromorphic nanowire device. Adv. Electr. Mater. 2, 1500458 (2016)

    Article  Google Scholar 

  23. Henderson, M.A.: A surface science perspective on TiO2 photocatalysis. Surf. Sci. Rep. 66, 185–297 (2011)

    Article  Google Scholar 

  24. Liu, G., Hoivik, N., Wang, X., Lu, S., Wang, K., Jakobsen, H.: Photoconductive, free-standing crystallized TiO2 nanotube membranes. Electrochim. Acta 93, 80–86 (2013)

    Article  Google Scholar 

  25. Pavlov, I.P.: Conditional reflexes: an investigation of the physiological activity of the cerebral cortex. Oxford University Press, New York (1927)

    Google Scholar 

  26. Feldman, D.E.: The spike-timing dependence of plasticity. Neuron 75, 556–571 (2012)

    Article  Google Scholar 

  27. Hartley, C.A., Phelps, E.A.: Fear models in animals and humans. In: Vasa, R.A., Roy, A.K. (eds.) Pediatric Anxiety Disorders: A Clinical Guide, pp. 3–21. Springer, New York, NY (2013)

    Chapter  Google Scholar 

  28. Pershin, Y.V., Di Ventra, M.: Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23, 881–886 (2010)

    Article  Google Scholar 

  29. Zidan, M.A., Fahmy, H.A.H., Hussain, M.M., Salama, K.N.: Memristor-based memory: the sneak paths problem and solutions. Microelectron. J. 44, 176–183 (2013)

    Article  Google Scholar 

  30. O’Kelly, C., Fairfield, J.A., Boland, J.J.: A single nanoscale junction with programmable multilevel memory. ACS Nano 8, 11724–11729 (2014)

    Article  Google Scholar 

  31. Janotti, A., Varley, J.B., Rinke, P., Umezawa, N., Kresse, G., Van de Walle, C.G.: Hybrid functional studies of the oxygen vacancy in TiO 2. Phys. Rev. B 81 (2010)

    Google Scholar 

  32. Jeong, D.S., Schroeder, H., Breuer, U., Waser, R.: Characteristic electroforming behavior in Pt/TiO 2/Pt resistive switching cells depending on atmosphere. J. Appl. Phys. 104, 123716 (2008)

    Article  Google Scholar 

  33. Kwon, D.H., Kim, K.M., Jang, J.H., Jeon, J.M., Lee, M.H., Kim, G.H., Li, X.S., Park, G.S., Lee, B., Han, S., Kim, M., Hwang, C.S.: Atomic structure of conducting nanofilaments in TiO 2 resistive switching memory. Nat. Nanotechnol. 5, 148–153 (2010)

    Article  Google Scholar 

  34. Jeong, D.S., Schroeder, H., Waser, R.: Mechanism for bipolar switching in a Pt/TiO 2/Pt resistive switching cell. Phys. Rev. B 79, 195317 (2009)

    Article  Google Scholar 

  35. Roose, B., Pathak, S., Steiner, U.: Doping of TiO 2 for sensitized solar cells. Chem. Soc. Rev. 44, 8326–8349 (2015)

    Article  Google Scholar 

  36. Szczepankiewicz, S.H., Colussi, A.J., Hoffmann, M.R.: Infrared spectra of photoinduced species on hydroxylated titania surfaces. J. Phys. Chem. B 9842–9850 (2000)

    Article  Google Scholar 

  37. Berger, T., Sterrer, M., Diwald, O., Knözinger, E., Panayotov, D., Thompson, T.L., Yates, J.T.: Light-induced charge separation in anatase TiO2 particles. J. Phys. Chem. B 109, 6061–6068 (2005)

    Article  Google Scholar 

  38. Zou, J., Zhang, Q., Huang, K., Marzari, N.: Ultraviolet photodetectors based on anodic TiO2 nanotube arrays. J. Phys. Chem. C 114, 10725–10729 (2010)

    Article  Google Scholar 

  39. Rasmussen, M.D., Molina, L.M., Hammer, B.: Adsorption, diffusion, and dissociation of molecular oxygen at defected TiO 2 (110): A density functional theory study. J. Chem. Phys. 120, 988–997 (2004)

    Article  Google Scholar 

  40. Xu, C., Niu, D., Muralimanohar, N., Balasubramonian, R., Zhang, T., Yu, S., Xie, Y.: Overcoming the challenges of crossbar resistive memory architectures. In: 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA), 7–11 Feb. 2015, pp. 476–488 (2015)

    Google Scholar 

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Authors and Affiliations

  1. ICYS-Namiki, National Institute for Materials Science, Tsukuba, Ibaraki, 305-0044, Japan

    Curtis J. O’Kelly

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  1. Curtis J. O’Kelly
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Correspondence to Curtis J. O’Kelly .

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Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA

    Leon Chua

  2. Democritus University of Thrace, Xanthi, Greece

    Georgios Ch. Sirakoulis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, UK

    Andrew Adamatzky

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O’Kelly, C.J. (2019). Associative Enhancement and Its Application in Memristor Based Neuromorphic Devices. In: Chua, L., Sirakoulis, G., Adamatzky, A. (eds) Handbook of Memristor Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-76375-0_19

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  • DOI: https://doi.org/10.1007/978-3-319-76375-0_19

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-76375-0

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