面向神经形态感知的人工脉冲神经元的研究进展

近年来，随着人工智能技术和脉冲神经网络(SNN)的迅猛发展，人工脉冲神经元的研究逐渐兴起。人工脉冲神经元的研究对于开发具有人类智能水平的机器人、实现自主学习和自适应控制等领域具有重要的应用前景。传统的电子器件由于缺乏神经元的非线性特性，需要复杂的电路结构和大量的器件才能模拟简单的生物神经元功能，同时功耗也较高。因此，最近研究者们借鉴生物神经元的工作机制，提出了多种基于忆阻器等新型器件的人工脉冲神经元方案。这些方案具有功耗低、结构简单、制备工艺成熟等优点，并且在模拟生物神经元的多种功能等方面取得了显著进展。文章将从人工脉冲神经元的基本原理出发，综述和分析目前已有的各种实现方案。具体来说，将分别介绍基于传统电子器件和基于新型器件的人工脉冲神经元的实现方案，并对其优缺点进行比较。此外，还将介绍不同类型的人工脉冲神经元在实现触觉、视觉、嗅觉、味觉、听觉和温度等神经形态感知方面的应用，并对未来的发展进行展望。希望能够为人工脉冲神经元的研究和应用提供有益的参考和启示。

Research Progress on Artificial Spiking Neurons for Neuromorphic Perception

The recent surge in artificial intelligence (AI) and spiking neural network (SNN) has generated a burgeoning interest among scholars in investigating artificial spiking neurons. This exploration holds immense promise in propelling robots toward attaining human-level intelligence, as well as facilitating autonomous learning and adaptive control. Conventional electronic devices lack the nuanced nonlinear behaviors inherent in neuromorphic systems, necessitating convoluted circuitry and a multitude of components to replicate even the simplest functions of biological neurons, all while consuming substantial amounts of power. Consequently, researchers have turned to the operational principles of biological neurons, devising novel artificial spiking neuron models leveraging emerging technologies like memristors. These innovative artificial spiking neurons offer notable advantages such as reduced power consumption, streamlined structures, and well-established fabrication processes, leading to substantial strides in emulating diverse biological neuron functions. This study comprehensively reviewed and analyzed various implementation strategies for artificial spiking neurons utilizing state-of-the-art neuromorphic devices. Moreover, it delved into the practical application of artificial spiking neurons in achieving neuromorphic perceptual capabilities encompassing touch, vision, olfaction, taste, audition, and temperature sensing. Finally, this work contemplated the future trajectory of this field, envisioning potential advancements and trends. By offering valuable insights and perspectives, this paper aims to serve as a reference guide, inspiring further research and practical utilization of artificial spiking neurons.