Artificial neural networks (ANNs) based on synaptic devices, which can simultaneously perform processing and storage of data, have superior computing performance compared to conventional von Neumann architectures. Here, we present a ferroelectric coupled artificial synaptic device with reliable weight update and storage properties for ANNs. The artificial synaptic device, which is based on a ferroelectric polymer capacitively coupled with an oxide dielectric via an electric-field-permeable, semiconducting single-walled carbon-nanotube channel, is successfully fabricated by inkjet printing. By controlling the ferroelectric polarization, synaptic dynamics, such as excitatory and inhibitory postsynaptic currents and long-term potentiation/depression characteristics, is successfully implemented in the artificial synaptic device. Furthermore, the constructed ANN, which is designed in consideration of the device-to-device variation within the synaptic array, efficiently executes the tasks of learning and recognition of the Modified National Institute of Standards and Technology numerical patterns.

中文翻译：

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铁电耦合碳纳米管晶体管的门可调突触动力学。

与传统的冯·诺依曼架构相比，基于突触设备的人工神经网络（ANN）可以同时执行数据的处理和存储，具有卓越的计算性能。在这里，我们提出了一种具有可靠的神经网络重量更新和存储特性的铁电耦合人工突触设备。通过喷墨印刷成功地制造了人工突触设备，该设备基于通过电场可渗透的半导体单壁碳纳米管通道与氧化物电介质电容耦合的铁电聚合物。通过控制铁电极化，在人工突触装置中成功实现了突触动力学，例如兴奋性和抑制性突触后电流以及长期的增强/抑制特性。此外，