Memristor is a kind of synaptic element with nanometer size and continuously variable memristance. The bridge synaptic circuit constructed by memristor has simple structure and precise control. In practice, because of the nonlinear characteristics of memristor, it will have a certain impact on the control of synaptic circuit and cause errors in weights. Therefore, a novel memristor synaptic circuit is proposed in this paper, the dual-mode memristor bridge synaptic neural network. The proposed method can make the weights more linear by controlling the input voltages, and make the outputs more linear by using symmetrical positive and negative pulses. Therefore, the proposed synaptic circuit is easier to be controlled. In this paper, the numerical simulations are conducted and verify the feasibility. Furthermore, the simulation experiments are conducted for edge extraction of grayscale birds images in the airport for bird recognition applied for the bird repelling applications.

中文翻译：

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双模忆阻器突触电路设计及在图像处理中的应用

忆阻器是一种具有纳米尺寸和连续可变忆阻的突触元件。忆阻器构成的桥式突触电路结构简单，控制精确。在实际应用中，由于忆阻器的非线性特性，会对突触电路的控制产生一定的影响，造成权重的误差。因此，本文提出了一种新型忆阻器突触电路，即双模忆阻器桥突触神经网络。所提出的方法可以通过控制输入电压使权重更加线性，并通过使用对称的正负脉冲使输出更加线性。因此，所提出的突触电路更易于控制。本文进行了数值模拟，验证了其可行性。此外，