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22 results on '"Luo, Yueguo"'

3. Spiking Neural P Systems with Minimal Parallelism

Author

Jiang, Yun, Luo, Fen, Luo, Yueguo, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, He, Cheng, editor, Mo, Hongwei, editor, Pan, Linqiang, editor, and Zhao, Yuxin, editor

Published
2017
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4. Timed Tissue P Systems With Channel States

Author

Luo, Yueguo, Zhao, Yuzhen, and Liu, Yi

Abstract

Tissue P systems with channel states are a variant of tissue P systems that can be employed as highly parallel computing devices, where the channel states can control the movements of objects. In a sense, the time-free approach can improve the robustness of P systems; hence, in this work, we introduce the time-free property into such P systems and explore their computational performances. Specifically, in a time-free manner, it is proved that this type of P systems have Turing universality by using two cells and four channel states with a maximum rule length of 2, or by using two cells and noncooperative symport rules with a maximum rule length of 1. Moreover, in terms of computational efficiency, it is proved that a uniform solution of the satisfiability ( $\mathcal {SAT}$ ) problem can be obtained in a time-free manner by applying noncooperative symport rules with a maximum rule length of 1. The research results of this paper show that a highly robust dynamic membrane computing system is constructed. Theoretically, relative to the existing system, our constructed system can enhance robustness and expand its application scope.

Published
2024
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7. Solving the SAT Problem by Cell-Like P Systems with Channel States and Symport Rules

Author

Wan, Xiaoming, Liu, Chuchuan, and Luo, Yueguo

Abstract

Cell-like P systems with channel states, which are a variant of tissue P systems in membrane computing, can be viewed as highly parallel computing devices based on the nested structure of cells, where communication rules are classified as symport rules and antiport rules. In this work, we remove the antiport rules and construct a novel variant, namely, cell-like P systems with channel states and symport rules, where one rule is only allowed to be nondeterministically applied once per channel. To explore the computational efficiency of the variant, we solve the SAT problem and obtain a uniform solution in polynomial time with the maximal length of rules 1. The results of our work are reflected in the following two aspects: first, communication rules are restricted to only one type, namely, symport rules; second, the maximal length of rules is decreased from 2 to 1. Our work indicates that the constructed variant with fewer rule types can still solve the SAT problem and obtain better results in terms of computational complexity. Hence, in terms of computational efficiency, our work is a notable improvement.

Published
2023
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19. The computational power of timed P systems with active membranes using promoters.

Author

LUO, YUEGUO, TAN, HAIJUN, ZHANG, YING, and JIANG, YUN

Subjects
PROMOTERS (Genetics), DEMETHYLATION
Abstract

P systems with active membranes are a class of bioinspired computing models, where the rules are used in the non-deterministic maximally parallel manner. In this paper, first, a new variant of timed P systems with active membranes is proposed, where the application of rules can be regulated by promoters with only two polarizations. Next, we prove that any Turing computable set of numbers can be generated by such a P system in the time-free way. Moreover, we construct a uniform solution to the $\mathcal{SAT}$ problem in the framework of such recognizer timed P systems in polynomial time, and the feasibility and effectiveness of the proposed system is demonstrated by an instance. Compared with the existing methods, the P systems constructed in our work require fewer necessary resources and RS-steps, which show that the solution is effective to NP -complete problem. [ABSTRACT FROM AUTHOR]

Published
2019
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22. Effectiveness of the Euclidean distance in high dimensional spaces.

Author

Xia, Shuyin, Xiong, Zhongyang, Luo, Yueguo, WeiXu, null, and Zhang, Guanghua

Subjects
*EUCLIDEAN distance, *RANDOM variables, *STOCHASTIC convergence, *DISTRIBUTION (Probability theory), *TOPOLOGICAL spaces
Abstract

This paper presents analysis of applicability and performance of the Euclidean distance in relation to the dimensionality of the space. The effect of dimensionality on the behavior of Euclidean distance is explored; Furthermore, it is shown that the minimum distance approaches the maximum distance under a broader set of conditions without requiring the calculation of variance of random variables. It is demonstrated that the minimum distance approaches the maximum distance even for some low dimensional distributions, such as normal distribution. Many proposed measures not based directly on Euclidean distance cannot enlarger the difference between closest point and farthest point. The analysis has been performed on a wide range of artificial and publicly available datasets. As the variables of different distributions have different convergence rates, the results should not be interpreted to mean that the Euclidean distance is not applicable. In fact, it is shown in experiments that the Euclidean distance is very useful in the noncentral t -distribution even for the dimensionality higher than 10,000. Furthermore, it is observed that the behavior of Euclidean distance becomes more useful with increased number of samples. [ABSTRACT FROM AUTHOR]

Published
2015
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