Mimicking Synaptic Plasticity and Neural Network Using Memtranstors,Advanced Materials

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Mimicking Synaptic Plasticity and Neural Network Using Memtranstors
Advanced Materials ( IF 27.4 ) Pub Date : 2018-02-05 , DOI: 10.1002/adma.201706717
Jian-Xin Shen _{1,

2} , Da-Shan Shang ₁ , Yi-Sheng Chai ₁ , Shou-Guo Wang ₃ , Bao-Gen Shen ₁ , Young Sun _{1,

2}

Affiliation

Artificial synaptic devices that mimic the functions of biological synapses have drawn enormous interest because of their potential in developing brain‐inspired computing. Current studies are focusing on memristive devices in which the change of the conductance state is used to emulate synaptic behaviors. Here, a new type of artificial synaptic devices based on the memtranstor is demonstrated, which is a fundamental circuit memelement in addition to the memristor, memcapacitor, and meminductor. The state of transtance (presented by the magnetoelectric voltage) in memtranstors acting as the synaptic weight can be tuned continuously with a large number of nonvolatile levels by engineering the applied voltage pulses. Synaptic behaviors including the long‐term potentiation, long‐term depression, and spiking‐time‐dependent plasticity are implemented in memtranstors made of Ni/0.7Pb(Mg_1/3Nb_2/3)O₃‐0.3PbTiO₃/Ni multiferroic heterostructures. Simulations reveal the capability of pattern learning in a memtranstor network. The work elucidates the promise of memtranstors as artificial synaptic devices with low energy consumption.

中文翻译：

使用Memtranstors模仿突触可塑性和神经网络

模仿生物突触功能的人工突触设备因其具有开发脑启发式计算的潜力而引起了极大的兴趣。当前的研究集中在忆阻装置中，其中电导状态的变化用于模拟突触行为。这里，展示了一种基于忆阻器的新型人工突触设备，它是除忆阻器，忆阻器和忆阻器之外的基本电路忆阻器。通过设计施加的电压脉冲，可以连续调节带有多个非易失性电平的，用作突触权重的跨膜晶体管的透射状态（由磁电电压表示）。突触行为包括长期增强，长期抑郁，_1/3 Nb _2/3）O ₃ -0.3PbTiO ₃ / Ni多铁性异质结构。仿真揭示了忆阻器网络中模式学习的能力。这项工作阐明了膜转运蛋白作为具有低能耗的人造突触装置的前景。

更新日期：2018-02-05

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