Abstract
This paper presents an electronic circuit able to emulate the behavior of a neural network based on memristive synapses. The latter is built with two flux-controlled floating memristor emulator circuits operating at high frequency and two passive resistors. Synapses are connected in a way that a bridge circuit is obtained, and its dynamical behavioral model is derived from characterizing memristive synapses. Analysis of the memristor characteristics for obtaining a suitable synaptic response is also described. A neural network of one neuron and two inputs is connected using the proposed topology, where synaptic positive and negative weights can easily be reconfigured. The behavior of the proposed artificial neural network based on memristors is verified through MATLAB, HSPICE simulations and experimental results. Synaptic multiplication is performed with positive and negative weights, and its behavior is also demonstrated through experimental results getting 6% of error.
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Notes
In this work, the minimum pulse width is 200 ns, which is governed by the st of the AD734 multiplier.
References
Parberry, I.: Circuit Complexity and Neural Networks. MIT Press, Cambridge (1994). ISBN 0-262-16148-6
Adamatzky, A., Chua, L.O.: Memristor Networks. Springer, Switzerland (2014). ISBN 978-3-319-02629-9
Hodgkin, A.L., Huxley, A.F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Phys. 117(4), 500–544 (1952)
Wang, Y., Ma, J., Xu, Y., Wu, F., Zhou, P.: The electrical activity of neurons subject to electromagnetic induction and gaussian white noise. Int. J. Bifurc. Chaos 27(02), 1750030 (2017)
Wu, F., Wang, C., Jin, W., Ma, J.: Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise. Phys. A 469(1), 81–88 (2017)
Ma, J., Mi, L., Zhou, P., Xu, Y., Hayat, T.: Phase synchronization between two neurons induced by coupling of electromagnetic field. Appl. Math. Comput. 307, 321–328 (2017)
Bostrom, N.: Superintelligence: Paths, Dangers, Strategies. Oxford University Press, Oxford (2014). ISBN 9780199678112
Wang, L., Li, L., Duan, D., Huang, T., Wang, H.: Pavlov associative memory in a memristive neural network and its circuit implementation. Neurocomputing 171(1), 23–29 (2016)
Pershin, Y.V., Di Ventra, M.: Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23(7), 88–886 (2010)
Yang, J., Wang, L., Wang, Y., Guo, T.: A novel memristive Hopfield neural network with application in associative memory. Neurocomputing 227, 142–148 (2017)
Sah, M.P., Yang, C., Kim, H., Chua, L.O.: A voltage mode memristor bridge synaptic circuit with memristor emulators. Sensors 12(3), 3587–3604 (2012)
Pavlov, I.P.: Conditioned reflexes: an investigation of the physiological activity of the cerebral cortex. A. Neurosci. 17(3), 136–141 (2010)
Chechik, G., Meilijson, I., Ruppin, E.: Effective learning requires neuronal remodeling of Hebbian synapses. Proc. Adv. Neural Inf. Process. Syst. 12(1), 1–7 (1999)
Strukov, D.B., Sneider, G.S., Stewart, D.R., Williams, R.S.: The missing memristor found. Nature 453(1), 80–83 (2008)
Zhang, Y., Wang, X., Li, Y., Friedman, E.G.: Memristive model for synaptic circuits. IEEE Trans. Circuits Syst. II: Express Briefs 64(7), 767–771 (2016)
Luo, L., Hu, X., Duan, S., Dong, Z., Wang, L.: Multiple memristor series-parallel connections with use in synaptic circuit design. IET Circuits Dev. Syst. 11(2), 123–134 (2017)
Adhikari, S.P., Yang, C., Kim, H., Chua, L.O.: Memristor bridge synapse-based neural network and its learning. IEEE Trans. Neural Net. Learn. Syst. 23(9), 1426–1435 (2012)
Kim, H., Sah, M.P., Yang, C., Roska, T., Chua, L.O.: Neural synaptic weighting with a pulse-based memristor circuit. IEEE Trans. Circuits Syst. I: Reg. Pap. 59(1), 148–158 (2012)
Wang, L., Wang, X., Duan, S., Li, H.: A spintronic memristor bridge synapse circuit and the application in memrisitive cellular automata. NeuroComputing 167, 346–351 (2015)
Low Cost Analog Multiplier, AD633, REV. B, Analog Devices (1999)
Sánchez-López, C., Mendoza-López, J., Carrasco-Aguilar, M.A., Muñiz-Montero, C.: A floating analog memristor emulator circuit. IEEE Trans. Circuits Syst. II: Express. Briefs 61(5), 309–313 (2014)
Sánchez-López, C., Carrasco-Aguilar, M.A., Muñiz-Montero, C.: A 16 Hz–160 kHz memristor emulator circuit. Int. J. Electron Commun. 69(9), 1208–1219 (2015)
Sánchez-López, C., Aguila-Cuapio, L.E.: A 860 kHz grounded memristor emulator circuit. Int. J. Electron Commun. 73, 11 (2017)
10 MHz Four-Quadrant Multiplier/Divider: AD734, REV. E, Analog Devices (2011)
Carro-Pérez, I., González-Hernández, H.G., Sánchez-López, C.: High-frequency memristive synapses. Proc. IEEE Int. Conf. Latin American Symp. Circuits Syst. 1(1), 1–4 (2017). https://doi.org/10.1109/LASCAS.2017.7948077
Hasler, P., Diorio, C., Minch, B.A., Mead, C.: Single transistor learning synapse with long term storage. IEEE Int. Symp. Circ. Syst. 1–4 (1995)
Data Sheet AD844AN: www.analog.com
Very High Speed, High Output Current, Voltage Feedback Amplifier, LM7171, Texas Instruments (2014)
Blackwell, G.R.: The Electronic Packaging Handbook. CRC Press, Boca Raton (1999). ISBN 9780849385919
Acknowledgements
This work was supported in part by the National Council for Science and Technology (CONACyT), Mexico, under Grant 222843; in part by the Universidad Autónoma de Tlaxcala (UATx), Tlaxcala de Xicohtencatl, TL, Mexico, under Grant CACyPI-UATx-2017; and in part by the Program to Strengthen Quality in Educational Institutions, under Grant C/PFCE-2016-29MSU0013Y-07-23.
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Carro-Pérez, I., Sánchez-López, C. & González-Hernández, H.G. Experimental verification of a memristive neural network. Nonlinear Dyn 93, 1823–1840 (2018). https://doi.org/10.1007/s11071-018-4291-1
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DOI: https://doi.org/10.1007/s11071-018-4291-1