具有突触规则的脉冲神经膜系统综述  

Survey on Spiking Neural P Systems with Rules on Synapses

作　　者：张露萍[1] 徐飞[1] ZHANG Lu-ping;XU Fei(Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China,School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学人工智能与自动化学院图像处理与智能控制教育部重点实验室,武汉430074

出　　处：《计算机科学》2022年第8期217-224,共8页Computer Science

基　　金：国家自然科学基金(62072201);国家重点研发计划-政府间国际科技创新合作项目(2021YFE0102100);湖北省重点研发计划项目(2021BAA168);中国博士后科学基金(2020M672359);中央高校基础科研专项基金(HUST:2019kfyXMBZ056)。

摘　　要：膜系统是受到细胞、组织、器官和系统的结构和功能的启发而提出的一类生物启发式计算模型。具有突触规则的脉冲神经膜系统是一类受神经元间信息交流方式的启发而提出的膜系统,该类模型中神经元是存储信息的单元,突触是整合并传递信息的媒介,整个系统采用分布式、并行方式处理信息。文中回顾了具有突触规则的脉冲神经膜系统的定义及相关概念,介绍了若干个脉冲神经膜系统变体,并对比了各系统的同异;列出了该系统及其变体在不同工作模式下计算能力方面的研究进展,以及该系统在求解计算困难问题、算术运算和破解密码方面的应用;提出了尚待研究的若干问题,以期为具有突触规则的脉冲神经膜系统理论研究提供方向,同时为相关系统的应用研究拓展思路。Membrane systems are a class of bio-inspired computing models,inspired by the structure and function of cells,tissue,organ and bio-systems.Spiking neural P systems with rules on synapses(SNPRS)are a type of membrane systems,inspired by the way that neurons communicate information.In SNPRS,each neuron is a basic unit for storing information,and each synapse is a medium for integrating and transmitting information.The whole system processes information in the distributed and parallel way.In this paper,we review the definition and related notions of SNPRS.Then,we introduce a few variants of SNPRS,and give a comparison among the variants of SNPRS.Furthermore,we provide results on the computation power of SNPRS(and their variants)working in different modes and on the application of the systems,such as solving NP-hard problems,implementing arithmetic operations,and breaking RSA.Additionally,some open problems are provided to suggest directions for further theore-tical as well as applicable research on SNPRS.

关 键 词：生物启发式计算 膜计算 脉冲神经膜系统 突触规则 计算能力 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]