星形胶质细胞脉冲神经系统生成的字符串语言

IF 0.4 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Fundamenta Informaticae Pub Date : 2015-07-01 DOI:10.3233/FI-2015-1154

Yuan Kong, Zheng Zhang, Yang Liu

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引用次数: 2

摘要

带有星形胶质细胞的脉冲神经系统(简称SNPA系统)是一类分布式并行计算设备，其灵感来自于脉冲沿着神经元之间的突触传递的方式。在这项工作中，我们研究了SNPA系统作为语言生成器的计算能力。具体地说，递归可枚举语言和正则语言的表示是通过SNPA系统在不忘记规则的情况下给出的。此外，还得到了一种简单的有限语言，该语言可以由SNPA系统生成，而通常的脉冲神经系统不能生成。这些结果表明星形胶质细胞是作为语言生成器的脉冲神经系统的强大成分。

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On String Languages Generated by Spiking Neural P Systems with Astrocytes

Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass along the synapses between neurons. In this work, we investigate the computational power of SNPA systems as language generators. Specifically, representations of recursively enumerable languages and of regular languages are given by means of SNPA systems without forgetting rules. Furthermore, a simple finite language is produced which can be generated by SNPA systems, while it cannot be generated by usual spiking neural P systems. These results show that the astrocytes are a powerful ingredient for spiking neural P systems as language generators.

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来源期刊

Fundamenta Informaticae 工程技术-计算机：软件工程

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

9.8 months

期刊介绍： Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing: solutions by mathematical methods of problems emerging in computer science solutions of mathematical problems inspired by computer science. Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, algebraic and categorical methods.