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Cellular neural networks — A tutorial on programmable nonlinear dynamics in space

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Analysis of Dynamical and Cognitive Systems

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 888))

Abstract

Cellular Neural/Nonlinear Networks (CNN) are analog, non-linear, mainly locally connected processor arrays placed on a multidimensional grid. In this tutorial the general framework and some application areas are described, mainly for mathematicians and physicists. The new invention, the CNN Universal Machine is exposed as well; its unique capability of implementing stored-programmable nonlinear spatial dynamics is highlighted. Finally, the first silicon VLSI implementations providing enormous computing power (in the order of 1012 operations per second on a single chip) are reviewed.

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References

  1. L.O.Chua and L.Yang, “Cellular neural networks: Theory,” IEEE Trans. Circuits and Systems, vol. 35, pp. 1257–72, 1988.

    Google Scholar 

  2. L.O.Chua and L.Yang, “Cellular neural networks: Applications,” IEEE Trans. Circuits and Systems, vol. 35, pp. 1273–90, 1988.

    Google Scholar 

  3. T.Roska and L.O.Chua, “Cellular neurl networks with non-linear and delay-type template elements,” Int. J. Circuit Theory and Applications, vol. 20, pp. 469–481, 1992.

    Google Scholar 

  4. L.O.Chua and T.Roska, “The CNN paradigm,” IEEE Trans. Circuits and Systems-I, vol. 40, pp. 147–156, March 1993.

    Google Scholar 

  5. T.Roska and L.O.Chua, “The CNN Universal Machine: An analogic array computer,” IEEE Trans. Circuits and Systems-II, vol. 40, pp. 163–173, March 1993.

    Google Scholar 

  6. Proc. First IEEE Int. Workshop on Cellular Neural Networks and their Applications (CNN-90), ed. T.Roska, 1990.

    Google Scholar 

  7. Proc. 2nd IEEE Int. Workshop on Cellular Neural Networks and their Applications, ed. J.A.Nossek, 1992.

    Google Scholar 

  8. Special Issue on Cellular Neural Networks (eds. J.Vandewalle and T.Roska), Int. J. Circuit Theory and Applications, vol. 20, Sept–Oct. 1992.

    Google Scholar 

  9. Special Issues on Cellular Neural Networks (eds. J.A.Nossek and T.Roska), IEEE Trans. Circuits and Systems, I: Fundamental theory and applications and II: Analog and digital signal processing, vol. 40, March 1993.

    Google Scholar 

  10. T.Roska and J.Vandewalle (eds.), Cellular Neural Networks, J.Wiley and Sons, Chichester, London, New York, 1993.

    Google Scholar 

  11. “The CNN Workstation User's Manual, Version 5.1,” Computer and Automation Institute of the Hung. Acad. Sci. (MTA-SzTAKI), Budapest, 1993.

    Google Scholar 

  12. T.Roska, L.O.Chua, and A.Zarándi, “Language, compiler, and operating system for the CNN supercomputer,” UCB/ERL Memo No. M93/93, Berkeley, California, April 1993.

    Google Scholar 

  13. A.Rodriguez-Vazquez et. al., “On a 16×16 CNN chip with optical sensors,” Internal report, Microelectronics Ceneter, University of Sevilla, Sevilla, 1993.

    Google Scholar 

  14. J.M.Cruz and L.O.Cuha, “Design high speed high density CNN's in CMOS technology,” CAS 1992

    Google Scholar 

  15. H.Harrer, J.A.Nossek, and R.Stelzl, “An analog implementation of discrete-time cellular neural networks,” IEEE Trans. Neural Networks, vol. 3, pp. 466–477, 1992.

    Google Scholar 

  16. K.Halonen, V.Porra, T.Roska, L.O.Chua, “VLSI implementation of a reconfigurable cellular neural network containing local logic (CNNL),” Int. J. Circuit Theory and Applications, vol. 20, pp. 573–582, 1992.

    Google Scholar 

  17. Internal reports of the Nonlinear Electronics Laboratory at ERL, U. C. Berkeley; private communication

    Google Scholar 

  18. A.Rodriguez-Vazquez, private communication

    Google Scholar 

  19. V.Pèrez-Muñuzurri, V.Pèrz-Villar, and L.O.Chua, “Autovawes for image processing on a two-dimensional array of Chua's circuits: flat and wrinkled labyrinths,” IEEE Trans. Circuits and Sytems, vol. 40, pp. 174–181, March, 1993.

    Google Scholar 

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Stig I. Andersson

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© 1995 Springer-Verlag Berlin Heidelberg

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Chua, L.O., Roska, T., Kozek, T. (1995). Cellular neural networks — A tutorial on programmable nonlinear dynamics in space. In: Andersson, S.I. (eds) Analysis of Dynamical and Cognitive Systems. Lecture Notes in Computer Science, vol 888. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58843-4_14

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  • DOI: https://doi.org/10.1007/3-540-58843-4_14

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  • Print ISBN: 978-3-540-58843-6

  • Online ISBN: 978-3-540-49113-2

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