Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET

被引:160
作者
Dutta, Sangya [1 ]
Kumar, Vinay [1 ]
Shukla, Aditya [1 ]
Mohapatra, Nihar R. [2 ]
Ganguly, Udayan [1 ]
机构
[1] Indian Inst Technol, Dept Elect Engn, Bombay 400076, Maharashtra, India
[2] IIT Gandhinagar, Dept Elect Engn, Gandhinagar 382355, India
关键词
SPIKING NEURONS;
D O I
10.1038/s41598-017-07418-y
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI-MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (similar to 10(11) neuron based) large neural networks.
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页数:7
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