Skip to main content

2018 | OriginalPaper | Buchkapitel

6. Advanced Neural Networks

verfasst von : Mark Skilton, Felix Hovsepian

Erschienen in: The 4th Industrial Revolution

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this chapter, we shall introduce various kinds of neural network architectures, including the infamous Convolutional network that showed how such networks when combined with the backpropagation algorithm for minimizing the errors was able to recognize handwritten characters, that was later used by the US postal service to recognize zip codes (post codes).

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Minsky, M. and Papert, S. (1969). Perceptrons. MIT Press. Minsky, M. and Papert, S. (1969). Perceptrons. MIT Press.
2.
Zurück zum Zitat Turing, A.M. (1952). The chemical basis of morphogenesis. Transactions. Royal Series B, Biological Sciences, 237 (641): 37–72. Turing, A.M. (1952). The chemical basis of morphogenesis. Transactions. Royal Series B, Biological Sciences, 237 (641): 37–72.
3.
Zurück zum Zitat Sieglmann and Sontag (1991). Applied Mathematics Letters, 4, 77–80. Sieglmann and Sontag (1991). Applied Mathematics Letters, 4, 77–80.
4.
Zurück zum Zitat Ackley, D.H., Hinton, G.E., and Sejnowski, T.J. (1985). A learning algorithm for Boltzmann machines. Cognitive Science, Elsevier, 9 (1): 147–169. Ackley, D.H., Hinton, G.E., and Sejnowski, T.J. (1985). A learning algorithm for Boltzmann machines. Cognitive Science, Elsevier, 9 (1): 147–169.
5.
Zurück zum Zitat Smolensky, P. (1986). Information processing in dynamical systems: Foundations of harmony theory. In Rumelhart, D. and McLelland, J.L. (1986) Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol.1, pp.194–281. MIT Press, Cambridge. Smolensky, P. (1986). Information processing in dynamical systems: Foundations of harmony theory. In Rumelhart, D. and McLelland, J.L. (1986) Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol.1, pp.194–281. MIT Press, Cambridge.
6.
Zurück zum Zitat Hinton, G.E. (2002). Training products of experts by minimizing contrastive divergence. Neural Computation, 14 (8): 1711–1800. Hinton, G.E. (2002). Training products of experts by minimizing contrastive divergence. Neural Computation, 14 (8): 1711–1800.
7.
Zurück zum Zitat Rumerlhart, D.E., Hinton, G.E., and Williams, R.J. (1986). Learning representations by back-propagating errors. Nature, 323 (9): 533–536. Rumerlhart, D.E., Hinton, G.E., and Williams, R.J. (1986). Learning representations by back-propagating errors. Nature, 323 (9): 533–536.
8.
Zurück zum Zitat Lecun, Y., Bottou, L., Bengio, Y., and Haffner, P. (2001). Gradient-based learning applied to document recognition. In Intelligent Signal Processing. IEEE Press, pp. 306–351. Lecun, Y., Bottou, L., Bengio, Y., and Haffner, P. (2001). Gradient-based learning applied to document recognition. In Intelligent Signal Processing. IEEE Press, pp. 306–351.
10.
Zurück zum Zitat Hochreiter, S., and Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9 (8): 1735–1780. Hochreiter, S., and Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9 (8): 1735–1780.
11.
Zurück zum Zitat Graves, A. et al. (2016). Hybrid computing using a neural network with dynamic external memory. Nature, 538, 471–476 (27 October 2016). Graves, A. et al. (2016). Hybrid computing using a neural network with dynamic external memory. Nature, 538, 471–476 (27 October 2016).
15.
Zurück zum Zitat Di Bono, M.G., and Zorzi, M. (2013). Deep generative learning location-invariant visual word recognition. Frontiers in Psychology, 4, 635. doi: 10.3389/fpsyg.2013.00635. Di Bono, M.G., and Zorzi, M. (2013). Deep generative learning location-invariant visual word recognition. Frontiers in Psychology, 4, 635. doi: 10.3389/fpsyg.2013.00635.
17.
Zurück zum Zitat Zadeh, L. (1965). Fuzzy logic. Information and Control, 8, 338–353. Zadeh, L. (1965). Fuzzy logic. Information and Control, 8, 338–353.
18.
Zurück zum Zitat Rezende, D.J., Mohamed, S., and Wierstra, D. (2014). Stochastic backpropagation and approximate inference in deep generative models. In ICML’2014. Preprint: arXiv:1401.4082. Rezende, D.J., Mohamed, S., and Wierstra, D. (2014). Stochastic backpropagation and approximate inference in deep generative models. In ICML’2014. Preprint: arXiv:1401.4082.
Metadaten
Titel
Advanced Neural Networks
verfasst von
Mark Skilton
Felix Hovsepian
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-62479-2_6