Ferroelectric FET-Based Implementation of FitzHugh-Nagumo Neuron Model

被引:12
|
作者
Rajasekharan, Dinesh [1 ]
Gaidhane, Amol [1 ]
Trivedi, Amit Ranjan [2 ]
Chauhan, Yogesh Singh [1 ]
机构
[1] Indian Inst Technol Kanpur, Dept Elect Engn, Kanpur 208016, Uttar Pradesh, India
[2] Univ Illinois, Dept Elect & Comp Engn, Chicago, CA 60607 USA
关键词
Neurons; Integrated circuit modeling; FeFETs; Transistors; Mathematical model; Computational modeling; Biological system modeling; FDSOI; ferroelectric; FitzHugh-Nagumo neuron; MOSFET; neuromorphic computing; neuron; winner-take-all (WTA); SYNCHRONIZATION; SPIKING; MEMORY; IMPACT;
D O I
10.1109/TCAD.2021.3101407
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Ferroelectric field-effect transistor (FeFET)-based circuit implementation mimicking FitzHugh-Nagumo neuron is proposed in this work. The proposed circuit is shown to mimic biological neuron properties, such as excitation block and anodal break excitation which are not mimicked by an integrate and fire neuron model. We also show a winner-take-all circuit that can be used with this proposed neuron implementation. The neuron implementation requires just one FeFET, three baseline field-effect transistors, and one capacitor, making it area and energy-efficient. The neuron circuit, with minimum sized transistors, consumes approximately 10 pJ per spike. The neuron's energy consumption per spike can be reduced to as low as 100 fJ by designing some of the transistors with aspect ratio less than one.
引用
收藏
页码:2107 / 2114
页数:8
相关论文
共 50 条
  • [1] A CMOS IMPLEMENTATION OF FITZHUGH-NAGUMO NEURON MODEL
    LINARES-BARRANCO, B
    SANCHEZ-SINENCIO, E
    RODRIGUEZVAZQUEZ, A
    HUERTAS, JL
    IEEE JOURNAL OF SOLID-STATE CIRCUITS, 1991, 26 (07) : 956 - 965
  • [2] Electronic Model of FitzHugh-Nagumo Neuron
    Petrovas, A.
    Lisauskas, S.
    Slepikas, A.
    ELEKTRONIKA IR ELEKTROTECHNIKA, 2012, 122 (06) : 117 - 120
  • [3] On a modification of the FitzHugh-Nagumo neuron model
    S. D. Glyzin
    A. Yu. Kolesov
    N. Kh. Rozov
    Computational Mathematics and Mathematical Physics, 2014, 54 : 443 - 461
  • [4] On a Modification of the FitzHugh-Nagumo Neuron Model
    Glyzin, S. D.
    Kolesov, A. Yu
    Rozov, N. Kh
    COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS, 2014, 54 (03) : 443 - 461
  • [5] Investigation of Microcontroller Based Model of FitzHugh-Nagumo Neuron
    Petrovas, Andrius
    Lisauskas, Saulius
    Slepikas, Alvydas
    PROCEEDINGS OF 15TH INTERNATIONAL CONFERENCE ON MECHATRONICS - MECHATRONIKA 2012, 2012, : 230 - 233
  • [6] An Analog Implementation of FitzHugh-Nagumo Neuron Model for Spiking Neural Networks
    Borwankar, Raunak
    Desai, Anurag
    Haider, Mohammad R.
    Ludwig, Reinhold
    Massoud, Yehia
    2018 16TH IEEE INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS), 2018, : 134 - 138
  • [7] A Low-Resource Digital Implementation of the Fitzhugh-Nagumo Neuron
    Leigh, Alexander J.
    Heidarpur, Moslem
    Mirhassani, Mitra
    PRIME 2022: 17TH INTERNATIONAL CONFERENCE ON PHD RESEARCH IN MICROELECTRONICS AND ELECTRONICS, 2022, : 297 - 300
  • [8] Nonadiabatic resonances in a noisy Fitzhugh-Nagumo neuron model
    Massanés, SR
    Vicente, CJP
    PHYSICAL REVIEW E, 1999, 59 (04) : 4490 - 4497
  • [9] Dynamical analysis of an improved FitzHugh-Nagumo neuron model with multiplier-free implementation
    Quan Xu
    Xiongjian Chen
    Bei Chen
    Huagan Wu
    Ze Li
    Han Bao
    Nonlinear Dynamics, 2023, 111 : 8737 - 8749
  • [10] Circuit implementation of FitzHugh-Nagumo neuron model using Field Programmable Analog Arrays
    Zhao, Jun
    Kim, Yong-Bin
    2007 50TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-3, 2007, : 648 - 651