Using Virus Machines to Compute Pairing Functions.

IF 6.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Neural Systems Pub Date : 2023-05-01 DOI:10.1142/S0129065723500235
Antonio Ramírez-de-Arellano, David Orellana-Martín, Mario J Pérez-Jiménez
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引用次数: 1

Abstract

Virus machines are computational devices inspired by the movement of viruses between hosts and their capacity to replicate using the resources of the hosts. This behavior is controlled by an external graph of instructions that opens different channels of the system to make viruses capable of moving. This model of computation has been demonstrated to be as powerful as turing machines by different methods: by generating Diophantine sets, by computing partial recursive functions and by simulating register machines. It is interesting to investigate the practical use cases of this model in terms of possibilities and efficiency. In this work, we give the basic modules to create an arithmetic calculator. As a practical application, two pairing functions are calculated by means of two different virus machines. Pairing functions are important resources in the field of cryptography. The functions calculated are the Cantor pairing function and the Gödel pairing function.

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使用病毒机计算配对函数。
病毒机是一种计算设备,其灵感来自于病毒在主机之间的移动,以及它们利用主机资源进行复制的能力。这种行为是由一个外部指令图控制的,它打开了系统的不同通道,使病毒能够移动。这个计算模型已经通过不同的方法被证明和图灵机一样强大:通过生成丢番图集,通过计算部分递归函数,通过模拟寄存器机。从可能性和效率的角度研究这个模型的实际用例是很有趣的。在这项工作中,我们给出了创建一个算术计算器的基本模块。在实际应用中,利用两种不同的病毒机计算两个配对函数。配对函数是密码学领域的重要资源。计算得到的函数是Cantor配对函数和Gödel配对函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Neural Systems
International Journal of Neural Systems 工程技术-计算机:人工智能
CiteScore
11.30
自引率
28.80%
发文量
116
审稿时长
24 months
期刊介绍: The International Journal of Neural Systems is a monthly, rigorously peer-reviewed transdisciplinary journal focusing on information processing in both natural and artificial neural systems. Special interests include machine learning, computational neuroscience and neurology. The journal prioritizes innovative, high-impact articles spanning multiple fields, including neurosciences and computer science and engineering. It adopts an open-minded approach to this multidisciplinary field, serving as a platform for novel ideas and enhanced understanding of collective and cooperative phenomena in computationally capable systems.
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