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The fourth element

Author

Listed:
  • James M. Tour

    (Computer Science, Mechanical Engineering and Materials Science, and the Smalley Institute for Nanoscale Science and Technology, Rice University, Houston, Texas 77005, USA. tour@rice.edu)

  • Tao He

    (Computer Science, Mechanical Engineering and Materials Science, and the Smalley Institute for Nanoscale Science and Technology, Rice University, Houston, Texas 77005, USA. tour@rice.edu)

Abstract

Almost four decades since its existence was first proposed, a fourth basic circuit element joins the canonical three. The 'memristor' might herald a step-change in the march towards ever more powerful circuitry.

Suggested Citation

  • James M. Tour & Tao He, 2008. "The fourth element," Nature, Nature, vol. 453(7191), pages 42-43, May.
    • Handle: RePEc:nat:nature:v:453:y:2008:i:7191:d:10.1038_453042a
    DOI: 10.1038/453042a
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    Citations

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    Cited by:

    1. Tu, Zhengwen & Ding, Nan & Li, Liangliang & Feng, Yuming & Zou, Limin & Zhang, Wei, 2017. "Adaptive synchronization of memristive neural networks with time-varying delays and reaction–diffusion term," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 118-128.
    2. Min, Fuhong & Zhang, Wen & Ji, Ziyi & Zhang, Lei, 2021. "Switching dynamics of a non-autonomous FitzHugh-Nagumo circuit with piecewise-linear flux-controlled memristor," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Chang, Wenting & Zhu, Song & Li, Jinyu & Sun, Kaili, 2018. "Global Mittag–Leffler stabilization of fractional-order complex-valued memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 346-362.
    4. Bao, Haibo & Park, Ju H. & Cao, Jinde, 2015. "Matrix measure strategies for exponential synchronization and anti-synchronization of memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 543-556.
    5. Xu, Wei & Zhu, Song & Fang, Xiaoyu & Wang, Wei, 2019. "Adaptive anti-synchronization of memristor-based complex-valued neural networks with time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    6. Xue, Yanmei & Zheng, Bo-Chao & Li, Tao & Li, Yuanlu, 2017. "Robust adaptive state feedback sliding-mode control of memristor-based Chua’s systems with input nonlinearity," Applied Mathematics and Computation, Elsevier, vol. 314(C), pages 142-153.
    7. Luo, Mengzhuo & Cheng, Jun & Liu, Xinzhi & Zhong, Shouming, 2019. "An extended synchronization analysis for memristor-based coupled neural networks via aperiodically intermittent control," Applied Mathematics and Computation, Elsevier, vol. 344, pages 163-182.
    8. Liu, Shuxin & Yu, Yongguang & Zhang, Shuo & Zhang, Yuting, 2018. "Robust stability of fractional-order memristor-based Hopfield neural networks with parameter disturbances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 845-854.
    9. Guo, Runan & Zhang, Ziye & Liu, Xiaoping & Lin, Chong, 2017. "Existence, uniqueness, and exponential stability analysis for complex-valued memristor-based BAM neural networks with time delays," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 100-117.
    10. Zhang, Lingzhong & Yang, Yongqing & Xu, Xianyun, 2018. "Synchronization analysis for fractional order memristive Cohen–Grossberg neural networks with state feedback and impulsive control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 644-660.
    11. Sakthivel, R. & Anbuvithya, R. & Mathiyalagan, K. & Ma, Yong-Ki & Prakash, P., 2016. "Reliable anti-synchronization conditions for BAM memristive neural networks with different memductance functions," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 213-228.
    12. Mathiyalagan, K. & Park, Ju H. & Sakthivel, R., 2015. "Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 967-979.
    13. Zhang, Lingzhong & Yang, Yongqing & Wang, Fei, 2017. "Projective synchronization of fractional-order memristive neural networks with switching jumps mismatch," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 402-415.
    14. Huaiqin Wu & Luying Zhang & Sanbo Ding & Xueqing Guo & Lingling Wang, 2013. "Complete Periodic Synchronization of Memristor-Based Neural Networks with Time-Varying Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-12, July.
    15. Lin, Dongyuan & Chen, Xiaofeng & Yu, Guoping & Li, Zhongshan & Xia, Yannan, 2021. "Global exponential synchronization via nonlinear feedback control for delayed inertial memristor-based quaternion-valued neural networks with impulses," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    16. Yang, Shuai & Hu, Cheng & Yu, Juan & Jiang, Haijun, 2021. "Projective synchronization in finite-time for fully quaternion-valued memristive networks with fractional-order," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    17. Usa Humphries & Grienggrai Rajchakit & Pramet Kaewmesri & Pharunyou Chanthorn & Ramalingam Sriraman & Rajendran Samidurai & Chee Peng Lim, 2020. "Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
    18. Shi, Yanchao & Cao, Jinde & Chen, Guanrong, 2017. "Exponential stability of complex-valued memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 313(C), pages 222-234.

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