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Memristor is defined as the fourth basic electronic element, the studies on its models exhibit diversity. Now, the matching extent between memristor model and natural memristor has received researchers' wide attention. A new memristor model is proposed by changing the ion diffusion term of the WOx memristor, namely, adding another two internal state variables τ and μ which denote the relaxation time and retention, respectively, and the improved model can simulate natural memristor better. Firstly, the new one is able to not only describe the general characteristics of a memrsitor, but also capture the memory loss behavior. In addition, the new memristor can be considered as a neural synapse, under the action of the input pulses with different amplitudes, duration and intervals, the spike rate dependent plasticity, short-term plasticity (STP), and long-term plasticity (LTP) are analyzed, and the ''learning experience'' phenomenon which is very similar to the biological system is discovered, most of which is due to the back diffusion of the oxygen vacancies during the intervals of the input pulses which are caused by the concentration difference. Moreover, an exponential decay equation is built to describe the relaxation process of STP. Finally, taking into consideration the relationship between temperature and ion diffusion coefficient, the effect of temperature on the relaxation process of STP is discussed. Experimental results show that the new memristor model can better match the actual behavior characteristics, and more suitably acts as a synapse for being applied to neuromorphic systems.
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Keywords:
- memristor /
- ion diffusion /
- synapse plasticity /
- temperature
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[11] Adhikari S P, Yang C J, Kim H, Chua L O 2012 IEEE Trans. Neural Networks and Learning Systems 23 1426
[12] Hu X F, Duan S K, Wang L D, Liao X F 2011 Sci. China: Inf. Sci. 41 500 (in Chinese) [胡小方, 段书凯, 王丽丹, 廖晓峰 2011 中国科学:信息科学 41 500]
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[20] Chang T, Jo S H, Kim K H, Sheridan P, Gaba S, Lu W 2011 Appl. Phys. A 102 857
[21] Chang T, Jo S H, Lu W 2011 ACS Nano 5 7669
[22] Ohno T, Hasegawa T, Tsuruoka T, Terabe K, Gimzewski J K, Aono M 2011 Nat. Mater. 10 591
[23] Wang Z Q, Xu H Y, Li X H, Yu H, Liu Y C, Zhu X J 2012 Adv. Funct. Mater. 22 2759
[24] Bhagya V, Srikumar B N, Raju T R, Shankaranarayana Rao B S 2015 J. Neurosci. Res. 93 104
[25] So H S, Choi S H, Seo K S, Seo C S, So S Y 2014 KSCE J. Civ. Eng. 18 2227
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[1] Chua L O 1971 IEEE Trans. Circ. Th. 18 507
[2] Strukov D B, Snider G S, Stewart D R, Williams R S 2008 Nature 453 80
[3] Biolek Z, Biolek D, Biolková V 2009 Radioengineering 18 210
[4] Chen Y R, Wang X B 2009 IEEE/ACM International Symposium on Nanoscale Architectures, San Francisco, CA USA, July 30-31, 2009 p7
[5] Wu H G, Bao B C, Chen M 2014 Chin. Phys. B 23 118401
[6] Jo S H, Kim K H, Lu W 2009 Nano Lett. 9 870
[7] Duan S K, Hu X F, Wang L D, Li C D, Mazumder P 2012 Sci. China: Inf. Sci. 55 1446
[8] Yener S C, Kuntman H H 2014 Radioengineering 23 1140
[9] Dong Z K, Duan S K, Hu X F, Wang L D, Li H 2014 Sci. World J. 2014 394828
[10] Cantley K D, Subramaniam A, Stiegler H J, Chapman R A, Vogel E M 2011 IEEE Trans. Nanotechnol. 10 1066
[11] Adhikari S P, Yang C J, Kim H, Chua L O 2012 IEEE Trans. Neural Networks and Learning Systems 23 1426
[12] Hu X F, Duan S K, Wang L D, Liao X F 2011 Sci. China: Inf. Sci. 41 500 (in Chinese) [胡小方, 段书凯, 王丽丹, 廖晓峰 2011 中国科学:信息科学 41 500]
[13] Afifi A, Ayatollahi A, Raissi F 2009 IEEE Circuit Theory and Design Antalya, August 23-27, 2009 p563
[14] Dong Z K, Duan S K, Hu X F, Wang L D 2014 Acta Phys. Sin. 63 128502 (in Chinese) [董哲康, 段书凯, 胡小方, 王丽丹 2014 63 128502]
[15] Tian X B, Xu H 2013 Chin. Phys. B 22 088501
[16] Tian X B, Xu H 2014 Chin. Phys. B 23 068401
[17] Xu H, Tian X B, Bu K, Li Q J 2014 Acta Phys. Sin. 63 098402 (in Chinese) [徐晖, 田晓波, 步凯, 李清江 2014 63 098402]
[18] Tian X B, Xu H, Li Q J 2014 Acta Phys. Sin. 63 048401 (in Chinese) [田晓波, 徐晖, 李清江 2014 63 048401]
[19] Chen L, Li C D, Huang T W, Ahmad H G, Chen Y R 2014 Phys. Lett. A 378 2924
[20] Chang T, Jo S H, Kim K H, Sheridan P, Gaba S, Lu W 2011 Appl. Phys. A 102 857
[21] Chang T, Jo S H, Lu W 2011 ACS Nano 5 7669
[22] Ohno T, Hasegawa T, Tsuruoka T, Terabe K, Gimzewski J K, Aono M 2011 Nat. Mater. 10 591
[23] Wang Z Q, Xu H Y, Li X H, Yu H, Liu Y C, Zhu X J 2012 Adv. Funct. Mater. 22 2759
[24] Bhagya V, Srikumar B N, Raju T R, Shankaranarayana Rao B S 2015 J. Neurosci. Res. 93 104
[25] So H S, Choi S H, Seo K S, Seo C S, So S Y 2014 KSCE J. Civ. Eng. 18 2227
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