Novel Highly Nonlinear Memristive Circuit Elements for Neural Networks

被引:0
|
作者
Liu, Tong [1 ]
Kang, Yuhong [1 ]
Verma, Mohini [1 ]
Orlowski, Marius [1 ]
机构
[1] Virginia Polytech Inst & State Univ, Bradley Dept Elect & Comp Engn, Blacksburg, VA 24061 USA
关键词
memristive switches; neural hardware; nonlinear circuits; spiking neuron;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Highly nonlinear dynamics arises from novel serially and antiserially connected memristive switches. Antiserially connected memristors offer a device with built-in spiking neuron behavior. Serially connected memristors offer new functionality of a cascade of sigmoid staircase curves to represent multi-level spike-timing dependent plasticity (STDP). In a programming operation, a serial arrangement of two switches displays multiple time-delays between threshold transitions showing three distinct current levels and an arrangement of three switches four current levels spanning 6 orders of magnitude. Anti-serially connected resistive switches, aka resistive floating electrode device (RFED), can generate well-controlled spikes as a result of the history of the dynamic input. Both types of composite switches can be packed into a single intersection of a memristive crossbar architecture of 4F(2). The switches have been manufactured as a multi-stack of Cu, TaOx, Pt materials with 32 nm of oxygen-deficient TaOx in a crossbar architecture.
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页数:8
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