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Hypergraph-Based Numerical Spiking Neural Membrane Systems with Novel Repartition Protocols.
Yin, Xiu; Liu, Xiyu; Sun, Minghe; Xue, Jie.
Afiliação
  • Yin X; Business School, Shandong Normal University, Jinan 250014, P. R. China.
  • Liu X; Business School, Shandong Normal University, Jinan 250014, P. R. China.
  • Sun M; College of Business, The University of Texas at San Antonio, San Antonio, TX 78249, USA.
  • Xue J; Business School, Shandong Normal University, Jinan 250014, P. R. China.
Int J Neural Syst ; 34(8): 2450039, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38715253
ABSTRACT
The classic spiking neural P (SN P) systems abstract the real biological neural network into a simple structure based on graphs, where neurons can only communicate on the plane. This study proposes the hypergraph-based numerical spiking neural membrane (HNSNM) systems with novel repartition protocols. Through the introduction of hypergraphs, the HNSNM systems can characterize the high-order relationships among neurons and extend the traditional neuron structure to high-dimensional nonlinear spaces. The HNSNM systems also abstract two biological mechanisms of synapse creation and pruning, and use plasticity rules with repartition protocols to achieve planar, hierarchical and spatial communications among neurons in hypergraph neuron structures. Through imitating register machines, the Turing universality of the HNSNM systems is proved by using them as number generating and accepting devices. A universal HNSNM system consisting of 41 neurons is constructed to compute arbitrary functions. By solving NP-complete problems using the subset sum problem as an example, the computational efficiency and effectiveness of HNSNM systems are verified.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Potenciais de Ação / Redes Neurais de Computação / Modelos Neurológicos / Neurônios Limite: Animals / Humans Idioma: En Revista: Int J Neural Syst Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Potenciais de Ação / Redes Neurais de Computação / Modelos Neurológicos / Neurônios Limite: Animals / Humans Idioma: En Revista: Int J Neural Syst Ano de publicação: 2024 Tipo de documento: Article