Abstract
Associative memory networks have been extensively studied to imitate the biological associative learning. The control circuits of most associative memory circuits are more complicated. Using the memristor with forgetting effect as a synapse can significantly reduce the complexity of the circuit. In this paper, an associative memory circuit based on a forgetting memristor is proposed to implement full-function Pavlov associative memory. The learning process and forgetting process in the Pavlov experiment, including forgetting under ringing stimuli, forgetting under food stimuli, and forgetting over time, can be achieved by the proposed circuit. The PSPICE simulation results demonstrate the effectiveness of the proposed circuit.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Chua, L.: Memristor-the missing circuit element. IEEE Trans. Circ. Theory 18(5), 507–519 (1971)
Strukov, D.B., Snider, G.S., Stewart, D.R., et al.: The missing memristor found. Nature 453(7191), 80–83 (2008)
Biolek, Z., Biolek, D., Biolkova, V.: SPICE model of memristor with nonlinear dopant drift. Radioengineering 18(2), 210–214 (2009)
Zhang, Y., Wang, X., Li, Y., et al.: Memristive model for synaptic circuits. IEEE Trans. Circ. Syst. II: Express Briefs 64(7), 767–771 (2017)
Guckert, L., Swartzlander, E.E.: MAD gatesmemristor logic design using driver circuitry. IEEE Trans. Circ. Syst. II: Express Briefs 64(2), 171–175 (2017)
Azghadi, M.R., Linares-Barranco, B., Abbott, D., et al.: A hybrid CMOS-memristor neuromorphic synapse. IEEE Trans. Biomed. Circ. Syst. 11(2), 434–445 (2017)
Wen, S., Xie, X., Yan, Z., et al.: General memristor with applications in multilayer neural networks. Neural Netw. 103, 142–149 (2018)
Kvatinsky, S., Ramadan, M., Friedman, E., Kolodny, A.: VTEAM-A general model for voltage controlled memristors. IEEE Trans. Circ. Syst. II: Express Briefs 62(8), 786–790 (2015)
Chen, L., Li, C., Huang, T., et al.: A synapse memristor model with forgetting effect. Phys. Lett. A 377(45–48), 3260–3265 (2013)
Zhou, E., Fang, L., Liu, R., et al.: An improved memristor model for brain-inspired computing. Chin. Phys. B 26(11), 118502 (2017)
Pershin, Y.V., Di Ventra, M.: Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23(7), 881–886 (2010)
Bichler, O., Zhao, W., Alibart, F., et al.: Pavlov’s dog associative learning demonstrated on synaptic-like organic transistors. Neural Comput. 25(2), 549–566 (2013)
Chen, L., Li, C., Wang, X., et al.: Associate learning and correcting in a memristive neural network. Neural Comput. Appl. 22(6), 1071–1076 (2013)
Wang, L., Li, H., Duan, S., et al.: Pavlov associative memory in a memristive neural network and its circuit implementation. Neurocomputing 171, 23–29 (2016)
Ma, D., Wang, G., Han, C., et al.: A memristive neural network model with associative memory for modeling affections. IEEE Access 6, 61614–61622 (2018)
Liu, X., Zeng, Z., Wen, S.: Implementation of memristive neural network with full-function pavlov associative memory. IEEE Trans. Circ. Syst. I: Regul. Pap. 63(9), 1454–1463 (2016)
Yang, L., Zeng, Z., Wen, S.: A full-function Pavlov associative memory implementation with memristance changing circuit. Neurocomputing 272, 513–519 (2018)
Wang, Z., Wang, X.: A novel memristor-based circuit implementation of full-function Pavlov associative memory accorded with biological feature. IEEE Trans. Circ. Syst. I: Regul. Pap. 65(7), 2210–2220 (2018)
Hu, X., Duan, S., Chen, G., et al.: Modeling affections with memristor-based associative memory neural networks. Neurocomputing 223, 129–137 (2017)
Acknowledgments
The work was supported by the National Natural Science Foundation of China under Grant 61571372, 61672436, and 61601376, the Fundamental Science and Advanced Technology Research Foundation of Chongqing cstc2017jcyjBX0050 and cstc2016jcyjA0547, the Fundamental Research Funds for the Central Universities under Grant XDJK2017A005 and XDJK2016A001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhou, M., Wang, L., Duan, S. (2019). An Improved Memristor-Based Associative Memory Circuit for Full-Function Pavlov Experiment. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11555. Springer, Cham. https://doi.org/10.1007/978-3-030-22808-8_60
Download citation
DOI: https://doi.org/10.1007/978-3-030-22808-8_60
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-22807-1
Online ISBN: 978-3-030-22808-8
eBook Packages: Computer ScienceComputer Science (R0)