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A Programmable Memristor Potentiometer and Its Application in the Filter Circuit

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Advances in Neural Networks - ISNN 2017 (ISNN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

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Abstract

Based on the electrical properties of memristor, the spintronic memristor is introduced into analog circuit design. Through programming the memristor by pulse signals, a programmable memristor potentiometer is designed in this paper. The potentiometer has the advantages of simple structure, small volume and continuous variable dynamic range. Based on the potentiometer above, this paper presents an amplifier circuit whose magnification is precisely adjustable and an active memristor-filter whose cut-off frequency and phase are adjustable as well. The circuit is characterized with smaller size, higher integration and lower power consumption, and its correctness and feasibility are verified by SPICE simulation. The research in this paper will promote the application of memristor in analog circuit, in addition, the performance of programmable memristor-analog circuit is satisfactory, which provides a new way for the integrated circuit design in the future.

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Southwest University, Chongqing, China

    Jinpei Tan, Shukai Duan, Ting Yang & Hangtao Zhu

Authors
  1. Jinpei Tan
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  2. Shukai Duan
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  3. Ting Yang
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  4. Hangtao Zhu
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Corresponding author

Correspondence to Shukai Duan .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Tan, J., Duan, S., Yang, T., Zhu, H. (2017). A Programmable Memristor Potentiometer and Its Application in the Filter Circuit. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-59081-3_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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