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Analysis of institutional authors

Song, TAuthorZeng, XxCorresponding Author

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September 6, 2021
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On the Computational Power of Asynchronous Axon Membrane Systems

Publicated to: IEEE Transactions on Emerging Topics in Computational Intelligence. 4 (5): 696-704 - 2020-10-01 4(5), DOI: 10.1109/TETCI.2019.2907724

Authors:

Song, T; Zheng, P; Wong, MLD; Jiang, M; Zeng, XX
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Affiliations

China Univ Petr, Coll Comp & Commun Engn, Qingdao 266580, Peoples R China - Author
Heriot Watt Univ, Putrajaya 62200, Malaysia - Author
Univ Canterbury, Dept Accounting & Informat Syst, Christchurch 8041, New Zealand - Author
Univ Politecn Madrid, Dept Artificial Intelligence, Madrid 28660, Spain - Author
Xiamen Univ, Dept Cognit Sci & Thchnol, Xiamen 361005, Peoples R China - Author
Xiamen Univ, Dept Comp Sci, Xiamen 361005, Peoples R China - Author
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Abstract

Axon membrane systems, also called axon P systems, are a group of neuron system inspired neural computing devices. The system are designed by the mimic of the way axon (connecting neurons in central nerves systems) processing impulse signals passing along it. In the systems, all the "computing units" are aligned one after another along the axon, achieving a linear topological structure. It was known that synchronous axon P systems can compute the families of Turing computable sets of both natural numbers and recursive functions. However, the computational power of asynchronous axon P systems is still open. In this paper, we investigate the computational power of asynchronous axon P systems, where the nonsynchronization is induced by either the node's asynchronously spiking (working in asynchronous mode) or the randomly assigned time consumption for each time spiking of the nodes (working in time-free mode). As results, it is proved that axon P systems working in either asynchronous or time-free mode are Turing universal as number generators, which indicates that the nonsynchronization will not reduce the computation power of axon P systems. It is worth noting that it needs O(n) spikes to encode natural number n in asynchronous axon P systems, but it needs O(n(2)) spikes in Turing universal synchronous axon P systems. These results partially answer an open problem left in [IEEE NNLS 26(11): 2816-29, 20151, and may also provide some hints on designing novel learning strategies by imposing computation tasks on the synapses of neural networks models.
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Keywords

Asynchronous modesAxon membrane systemComputability and decidabilityComputation powerComputation tasksComputational powerLearning strategyLearning systemsMembrane computingNatural computingNetworksNeural computingNeural networksNeural networks modelNeural p systemsNon-synchronizationNumber theoryRecursive functionsSatSpiking neuronsTopological structureUniversality

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal IEEE Transactions on Emerging Topics in Computational Intelligence due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2020, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Control and Optimization. Notably, the journal is positioned above the 90th percentile.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-09:

  • WoS: 8
  • Scopus: 10
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-09:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 6 (PlumX).
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: China; Malaysia; New Zealand.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (SONG, TAO) and Last Author (ZENG, XIANGXIANG).

the author responsible for correspondence tasks has been ZENG, XIANGXIANG.

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Awards linked to the item

The work of T. Song was supported in part by the Tai Shan Scholar Foundation, National Natural Science Foundation of China under Grant 61873280, Grant 61672033, and Grant 61672248; in part by the Key Research and Development Program of Shandong Province under Grant 2017GGX10147, in part by the Natural Science Foundation of Shandong Province under Grant ZR2017MF004, in part by the Fundamental Research Funds for the Central Universities under Grant 18CX02152A, Project TIN2016-81079-R (MINECO AEI/FEDER, Spain-EU), and the InGEMICS-CM Project (B2017/BMD-3691, FSE/FEDER, Comunidad deMadrid-EU), Research Project TIN2016-81079-R (AEI/FEDER, Spain-EU), and Grant 2016-T2/TIC-2024 from Talento-Comunidad de Madrid. The work of X. Zeng was supported in part by the Juan de la Cierva position (code: IJCI-2015-26991), and in part by the President Fund of Xiamen University under Grant 20720170054.
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