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2017 | OriginalPaper | Chapter

Hardware Spiking Artificial Neurons, Their Response Function, and Noises

Author : Doo Seok Jeong

Published in: Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices

Publisher: Springer India

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Abstract

In this chapter, overviewed are hardware-based spiking artificial neurons that code neuronal information by means of action potential, viz. spike, in hardware artificial neural networks (ANNs). Ongoing attempts to realize neuronal behaviours on Si ‘to a limited extent’ are addressed in comparison with biological neurons. Note that ‘to a limited extent’ in this context implicitly means ‘sufficiently’ for realizing key features of neurons as information processors. This ambiguous definition is perhaps open to a question as to what neuronal behaviours the key features encompass. The key features are delimited within the framework of neuromorphic engineering, and thus, they approximately are (i) integrate-and-fire; (ii) neuronal response function, i.e. spike-firing rate change upon synaptic current; and (iii) noise in neuronal response function. Hardware-based spiking artificial neurons are aimed to achieve these goals that are ambitious albeit challenging. Overviewing a number of attempts having made up to now illustrates approximately two seemingly different approaches to the goal: a mainstream approach with conventional active circuit elements, e.g. complementary metal-oxide-semiconductor (CMOS), and an emerging one with monostable resistive switching devices, i.e. threshold switches. This chapter will cover these approaches with particular emphasis on the latter. For instance, available types of threshold switches, which are classified upon underlying physics will be dealt with in detail.

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Literature
1.
go back to reference Averbeck, B.B., Latham, P.E., Pouget, A.: Nat. Rev. Neurosci. 7, 358–366 (2006)CrossRef Averbeck, B.B., Latham, P.E., Pouget, A.: Nat. Rev. Neurosci. 7, 358–366 (2006)CrossRef
3.
go back to reference Indiveri, G., Linares-Barranco, B., Hamilton, T.J., van Schaik, A., Etienne-Cummings, R., Delbruck, T., Liu, S.-C., Dudek, P., Häfliger, P., Renaud, S., Schemmel, J., Cauwenberghs, G., Arthur, J., Hynna, K., Folowosele, F., Saighi, S., Serrano-Gotarredona, T., Wijekoon, J., Wang, Y., Boahen, K.: Front. Neurosci. 5, 1–23 (2011) Indiveri, G., Linares-Barranco, B., Hamilton, T.J., van Schaik, A., Etienne-Cummings, R., Delbruck, T., Liu, S.-C., Dudek, P., Häfliger, P., Renaud, S., Schemmel, J., Cauwenberghs, G., Arthur, J., Hynna, K., Folowosele, F., Saighi, S., Serrano-Gotarredona, T., Wijekoon, J., Wang, Y., Boahen, K.: Front. Neurosci. 5, 1–23 (2011)
4.
go back to reference Hamann, C.H., Hamnett, A., Vielstich, W.: Electrochemistry, 2nd edn. WILEY-VCH Verlag GmbH & Co., Weinheim (2007) Hamann, C.H., Hamnett, A., Vielstich, W.: Electrochemistry, 2nd edn. WILEY-VCH Verlag GmbH & Co., Weinheim (2007)
6.
go back to reference Jeong, D.S., Kim, I., Ziegler, M., Kohlstedt, H.: RSC Adv. 3, 3169–3183 (2013)CrossRef Jeong, D.S., Kim, I., Ziegler, M., Kohlstedt, H.: RSC Adv. 3, 3169–3183 (2013)CrossRef
8.
go back to reference Dayan, P., Abbott, L.F.: Theoretical Neuroscience. The MIT Press, London (2001)MATH Dayan, P., Abbott, L.F.: Theoretical Neuroscience. The MIT Press, London (2001)MATH
10.
12.
go back to reference Ma, W.J., Beck, J.M., Latham, P.E., Pouget, A.: Nat. Neurosci. 9, 1432–1438 (2006)CrossRef Ma, W.J., Beck, J.M., Latham, P.E., Pouget, A.: Nat. Neurosci. 9, 1432–1438 (2006)CrossRef
14.
go back to reference Bialek, W., Rieke, F.: de Ruyter van Steveninck R. Warland D. Science 252, 1854–1857 (1991) Bialek, W., Rieke, F.: de Ruyter van Steveninck R. Warland D. Science 252, 1854–1857 (1991)
16.
17.
go back to reference Eliasmith, C., Anderson, C.H.: Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems. MIT Press, Cambridge, MA (2003) Eliasmith, C., Anderson, C.H.: Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems. MIT Press, Cambridge, MA (2003)
18.
go back to reference Anderson, C.: Computational Intelligence Imitating Life. IEEE Press, New York (1994) Anderson, C.: Computational Intelligence Imitating Life. IEEE Press, New York (1994)
19.
go back to reference Pouget, A., Dayan, P., Zemel, R.S.: Annu. Rev. Neurosci. 26, 381–410 (2003)CrossRef Pouget, A., Dayan, P., Zemel, R.S.: Annu. Rev. Neurosci. 26, 381–410 (2003)CrossRef
20.
go back to reference Weiss, Y., Fleet, D.J.: Velocity Likelihoods in Biological and Machine Vision. In Statistical Theories of the Cortex. MIT Press, Cambridge, MA (2002) Weiss, Y., Fleet, D.J.: Velocity Likelihoods in Biological and Machine Vision. In Statistical Theories of the Cortex. MIT Press, Cambridge, MA (2002)
21.
go back to reference Lim, H., Kornijcuk, V., Seok, J.Y., Kim, S.K., Kim, I., Hwang, C.S., Jeong, D.S.: Sci. Rep. (2015) Lim, H., Kornijcuk, V., Seok, J.Y., Kim, S.K., Kim, I., Hwang, C.S., Jeong, D.S.: Sci. Rep. (2015)
22.
go back to reference Lapicque, L.: J. Physiol. Pathol. Gen. 9, 620–635 (1907) Lapicque, L.: J. Physiol. Pathol. Gen. 9, 620–635 (1907)
24.
go back to reference Gerstner, W., Kistler, W.M.: Spiking Neuron Models: Single Neurons, Populations. Cambridge University Press, Plasticity (2002)CrossRefMATH Gerstner, W., Kistler, W.M.: Spiking Neuron Models: Single Neurons, Populations. Cambridge University Press, Plasticity (2002)CrossRefMATH
25.
go back to reference Jolivet, R., Lewis, T.J., Gerstner, W.: Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy, vol 92. vol 2. doi:10.1152/jn.00190.2004 (2004) Jolivet, R., Lewis, T.J., Gerstner, W.: Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy, vol 92. vol 2. doi:10.​1152/​jn.​00190.​2004 (2004)
28.
30.
31.
go back to reference Mead, C.: Analog VLSI and Neural Systems. Adison-Wesley, Reading, MA (1989)MATH Mead, C.: Analog VLSI and Neural Systems. Adison-Wesley, Reading, MA (1989)MATH
33.
go back to reference Indiveri, G., Chicca, E., Douglas, R.: IEEE Trans. Neural Netw. 17, 211–221 (2006)CrossRef Indiveri, G., Chicca, E., Douglas, R.: IEEE Trans. Neural Netw. 17, 211–221 (2006)CrossRef
34.
go back to reference Pickett, M.D., Medeiros-Ribeiro, G., Williams, R.S.: Nat. Mater. 12, 114–117 (2012)CrossRef Pickett, M.D., Medeiros-Ribeiro, G., Williams, R.S.: Nat. Mater. 12, 114–117 (2012)CrossRef
36.
go back to reference Jeong, D.S., Thomas, R., Katiyar, R.S., Scott, J.F., Kohlstedt, H., Petraru, A., Hwang, C.S.: Rep. Prog. Phys. 75, 076502 (2012)CrossRef Jeong, D.S., Thomas, R., Katiyar, R.S., Scott, J.F., Kohlstedt, H., Petraru, A., Hwang, C.S.: Rep. Prog. Phys. 75, 076502 (2012)CrossRef
37.
go back to reference Jeong, D.S., Lim, H., Park, G.-H., Hwang, C.S., Lee, S.: Cheong B-k. J. Appl. Phys. 111, 102807 (2012)CrossRef Jeong, D.S., Lim, H., Park, G.-H., Hwang, C.S., Lee, S.: Cheong B-k. J. Appl. Phys. 111, 102807 (2012)CrossRef
39.
go back to reference Lee, M.-J., Lee, D., Cho, S.-H., Hur, J.-H., Lee, S.-M., Seo, D.H., Kim, D.-S., Yang, M.-S., Lee, S., Hwang, E., Uddin, M.R., Kim, H., Chung, U.I., Park, Y., Yoo, I.-K.: Nat. Commun. 4, 2629 (2013) Lee, M.-J., Lee, D., Cho, S.-H., Hur, J.-H., Lee, S.-M., Seo, D.H., Kim, D.-S., Yang, M.-S., Lee, S., Hwang, E., Uddin, M.R., Kim, H., Chung, U.I., Park, Y., Yoo, I.-K.: Nat. Commun. 4, 2629 (2013)
40.
go back to reference Ahn, H.-W., Jeong, D.S., Cheong, B.-K., Kim, S.-D., Shin, S.-Y., Lim, H., Kim, D., Lee, S.: ECS Solid State Lett. 2, N31–N33 (2013) Ahn, H.-W., Jeong, D.S., Cheong, B.-K., Kim, S.-D., Shin, S.-Y., Lim, H., Kim, D., Lee, S.: ECS Solid State Lett. 2, N31–N33 (2013)
42.
go back to reference Cario, L., Vaju, C., Corraze, B., Guiot, V., Janod, E.: Adv. Mater. 22, 5193–5197 (2010)CrossRef Cario, L., Vaju, C., Corraze, B., Guiot, V., Janod, E.: Adv. Mater. 22, 5193–5197 (2010)CrossRef
44.
45.
go back to reference Liu, X., Sadaf, S.M., Son, M., Shin, J., Park, J., Lee, J., Park, S., Hwang, H.: Nanotechnology 22, 475702 (2011)CrossRef Liu, X., Sadaf, S.M., Son, M., Shin, J., Park, J., Lee, J., Park, S., Hwang, H.: Nanotechnology 22, 475702 (2011)CrossRef
46.
go back to reference Bienenstock, E., Cooper, L., Munro, P.: J. Neurosci. 2, 32–48 (1982) Bienenstock, E., Cooper, L., Munro, P.: J. Neurosci. 2, 32–48 (1982)
47.
48.
go back to reference DerChang, K., Tang, S., Karpov, I.V., Dodge, R., Klehn, B., Kalb, J.A., Strand, J., Diaz, A., Leung, N., Wu, J., Lee, S., Langtry, T., Kuo-wei, C., Papagianni, C., Jinwook, L., Hirst, J., Erra, S., Flores, E., Righos, N., Castro, H.: Spadini G A stackable cross point Phase Change Memory. In: IEEE International Electron Devices Meeting, vol. 7–9, pp. 1–4 (2009) DerChang, K., Tang, S., Karpov, I.V., Dodge, R., Klehn, B., Kalb, J.A., Strand, J., Diaz, A., Leung, N., Wu, J., Lee, S., Langtry, T., Kuo-wei, C., Papagianni, C., Jinwook, L., Hirst, J., Erra, S., Flores, E., Righos, N., Castro, H.: Spadini G A stackable cross point Phase Change Memory. In: IEEE International Electron Devices Meeting, vol. 7–9, pp. 1–4 (2009)
49.
go back to reference 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.: Science 345, 668–673 (2014)CrossRef 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.: Science 345, 668–673 (2014)CrossRef
50.
go back to reference Gehlhaar, J.: Neuromorphic processing: a new frontier in scaling computer architecture. In: Architectural Support for Programming Languages and Operating Systems, Salt Lake City, UT, USA, pp. 317–318 (2014) Gehlhaar, J.: Neuromorphic processing: a new frontier in scaling computer architecture. In: Architectural Support for Programming Languages and Operating Systems, Salt Lake City, UT, USA, pp. 317–318 (2014)
Metadata
Title
Hardware Spiking Artificial Neurons, Their Response Function, and Noises
Author
Doo Seok Jeong
Copyright Year
2017
Publisher
Springer India
DOI
https://doi.org/10.1007/978-81-322-3703-7_1