标题： 当代脉冲生物启发神经网络的实现 显示英文标题

标题： Contemporary implementations of spiking bio-inspired neural networks

摘要： 该领域脉冲神经网络的广泛发展导致了许多对人们生活有直接影响的研究领域。 作为所有神经网络中最生物相似的，脉冲神经网络不仅允许解决识别和聚类问题（包括动态问题），还促进了对人类神经系统日益增长的知识。 我们的分析表明，硬件实现非常重要，因为网络单元中的物理过程特性会影响它们模拟活神经组织的神经活动的能力，以及信息处理、存储和传输某些阶段的效率。 本综述回顾了在“半导体”、“超导体”和“光学”领域中现有生物启发脉冲网络的硬件类脑实现。 特别关注不同方法有效“混合”的可能性。 显示英文摘要

摘要： The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people's lives. As the most bio-similar of all neural networks, spiking neural networks not only allow the solution of recognition and clustering problems (including dynamics), but also contribute to the growing knowledge of the human nervous system. Our analysis has shown that the hardware implementation is of great importance, since the specifics of the physical processes in the network cells affect their ability to simulate the neural activity of living neural tissue, the efficiency of certain stages of information processing, storage and transmission. This survey reviews existing hardware neuromorphic implementations of bio-inspired spiking networks in the "semiconductor", "superconductor" and "optical" domains. Special attention is given to the possibility of effective "hybrids" of different approaches