Adaptive response to the timely constant stimulus is the common feature of real neurons. The circuit of the adaptive neuron model consumes less power and requires less data transmission bandwidth compared to the circuit of the non-adaptive neuron model, especially for encoding time-varying signals. Memristor is a good candidate for mimicking the behavior of neurons so that the simple memristor-based circuit can directly emulate many specific behaviors of the neurons with low power and low area consumption. In this work, for the first time, we show that as the nonvolatile switching property of the memristor can be useful for representing long-term adaptation behavior in the memristor-based neuron, the short-term adaptation behavior can also be emulated directly using the same memristor-based circuit due to the volatile switching property of the memristor. Here, short term adaptation is realized using the volatile property of memristor, unlike neuron circuits where adaptation is realized using leakage modulation. As a result, in the memristor-based neuron extra power dissipation can be reduced. Two different types of memristors are used for implementing the proposed circuit of adaptive leaky integrate-and-fire neuron, the volatile/non-volatile memristor and threshold switching memristor are in the charge and discharge path of the capacitor, respectively. Results show that the volatile or non-volatile resistance change of charging memristor upon different input patterns to the neuron circuit determines the type of adaptive behavior of the neuron response, i.e. the neuron may show short-term adaptation or long-term adaptation or does not show an adaptation behavior at all. Comparison with similar works shows that the energy consumption per spiking of the proposed neuron is relatively low, while the circuit is very area-efficient.

对及时的恒定刺激的适应性反应是真实神经元的共同特征。与非自适应神经元模型的电路相比，自适应神经元模型的电路消耗更少的功率并且需要更少的数据传输带宽，特别是对于编码时变信号。忆阻器是模拟神经元行为的良好候选者，因此简单的基于忆阻器的电路可以以低功耗和低面积消耗直接模拟神经元的许多特定行为。在这项工作中，我们首次表明忆阻器的非易失性开关特性可用于表示基于忆阻器的神经元的长期适应行为，由于忆阻器的易失性开关特性，也可以使用相同的基于忆阻器的电路直接模拟短期适应行为。在这里，短期适应是使用忆阻器的易失性实现的，不像神经元电路使用泄漏调制来实现适应。结果，在基于忆阻器的神经元中，可以减少额外的功耗。两种不同类型的忆阻器用于实现所提出的自适应泄漏积分触发神经元电路，易失性/非易失性忆阻器和阈值切换忆阻器分别位于电容器的充电和放电路径中。结果表明，充电忆阻器对神经元电路的不同输入模式下的易失性或非易失性电阻变化决定了神经元响应的适应性行为类型，即神经元可能表现出短期适应或长期适应或不表现完全表现出适应行为。与类似工作的比较表明，所提出的神经元每次脉冲的能量消耗相对较低，而电路的面积效率很高。