Oscillatory neural associative memories with synapses based on memristor bridges

Chua, L., Memristor–the Missing circuit element, IEEE Trans. Circuit Theory, 1971, vol. 18, pp. 507–519.

Strukov, D.B., Snider, G.S., Stewart, D.R., and Williams, R.S., The Missing memristor found, Nature, 2008, vol. 453, pp. 80–83.

http://www.utmn.ru/presse/teleradiokanal-evrazion/videonovosti-tyumgu/89986/#.

Pershin, Y. and Di Ventra, M., Experimental demonstration of associative memory with memristive neural networks, Neural Networks, 2010, vol. 23, pp. 881–886.

Wu, A., Zhang, J., and Zeng, Z., Dynamic behaviors of a class of memristor-based Hopfield networks, Phys. Lett. A, 2011, vol. 375, pp. 1661–1665.

Liu, B., Chen, Y., Wysocki, B., and Huang, T., Reconfigurable neuromorphic computing system with memristor- based synapse design, Neural Process. Lett., 2015, vol. 41, pp. 159–167.

Nishikawa, T., Hoppensteadt, F.C., and Lai Y.-C., Oscillatory associative memory network with perfect retrieval, Physica D, 2004, vol. 197, pp. 134–148.

Chua, L., Resistance switching memories are memristors, Appl. Phys. A: Mater. Sci. Process., 2011, vol. 102, pp. 765–783.

Ho, Y., Huang, G.M., and Li, P., Nonvolatile memristor memory: Device characteristics and design applications, Proc. of IEEE/ACM Int. Conf. on Computer-Aided Design (ICCAD), 2009, pp. 485–490.

Jo, S.H., Chang, T., Ebong, I., Bhadviya, B.B., Mazumder, P., and Lu, W., Nanoscale memristor device as synapse in neuromorphic systems, Nanoletters, 2010, vol. 10, pp. 1297–1301.

Kavehei, O., Memristive devices and circuits for computing, memory, and neuromorphic applications, PhD Thesis, Australia: The University of Adelaida, 2011.

Lehtonen, E., Memristive Computing, Finland: University of Turku, 2012.

Wu, Q., Liu, B., Chen, Y., Li, H., Chen, Q., and Qiu, Q., Bio-inspired computing with resistive memories–Models, architectures and applications, Proc. of 2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014, pp. 834–837.

Tarkov, M.S., Mapping weight matrix of a neural network’s layer onto memristor crossbar, Opt. Mem. Neural Networks (Inform. Optics), 2015, vol. 24, pp. 109–115.

Kim, H., Sah, M.P., Yang, C., Roska, T., and Chua, L.O., Memristor bridge-based artificial neural weighting circuit, Memristor Networks, Switzerland: Springer, 2014, pp. 249–266.

LTSPICE IV. http://ecee.colorado.edu/~mathys/ecen1400/pdf/scad3.pdf.

Wagner, P., The LTspice2Matlab Function. http://www.mathworks.com/matlabcentral /fileexchange/23394- fast-import-of-compressed-binary-raw-files-created-with-ltspice-circuit-simulator.

Dorran, D., The RunLTspice Function. https://dadorran.wordpress.com/tag/run-ltspice-matlab/.

Biolek, Z., Biolek, D., and Biolkova, V., SPICE model of memristor with nonlinear dopant drift, Radioengineering, 2009, vol. 18, pp. 210–214.

Falatic, M., Memristor simulation with LTspice. http://www.falatic.com/index.php/69.

Osowski S., Neironnye seti dlya obrabotki informatsii (Neural Networks for Information Processing), Moskwa: Finansy i statistika, 2002 [in Russian].