Energy consumption remains the main limiting factors in many IoT applications. In particular, micro-controllers consume far too much power. In order to overcome this problem, new circuit designs have been proposed and the use of spiking neurons and analog computing has emerged as it allows a very significant consumption reduction. However, working in the analog domain brings difficulty to handle the sequential processing of incoming signals as is needed in many use cases. In this paper, we use a bio-inspired phenomenon called Interacting Synapses to produce a time filter, without using non-biological techniques such as synaptic delays. We propose a model of neuron and synapses that fire for a specific range of delays between two incoming spikes, but do not react when this Inter-Spike Timing is not in that range. We study the parameters of the model to understand how to choose them and adapt the Inter-Spike Timing. The originality of the paper is to propose a new way, in the analog domain, to deal with temporal sequences.

翻译：能耗仍是许多物联网应用的主要限制因素，尤其是微控制器功耗过高。为解决这一问题，研究者提出了新型电路设计，其中脉冲神经元与模拟计算因其能显著降低功耗而备受关注。然而，模拟域处理信号时难以实现许多应用场景所需的时序顺序处理。本文受生物启发，利用名为"交互突触"的生物现象构建时间滤波器，无需采用突触延迟等非生物技术。我们提出一种神经元-突触模型，该模型仅在两个输入脉冲的特定时间间隔范围内产生发放，而对超出该范围的脉冲间隔不响应。通过研究模型参数，我们揭示了如何选择参数并适配脉冲间隔。本文创新之处在于提出了一种在模拟域处理时间序列的新方法。