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Spiking Neural P Systems with Anti-spikes Based on the Min-Sequentiality Strategy

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Bio-inspired Computing: Theories and Applications (BIC-TA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 951))

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Abstract

Membrane computing models based on cell structure and function have important applications in computer science and provide new theories and methods for modeling biological systems. The spiking neural P system based on the min-sequentiality strategy is a special kind of membrane computing model. Anti-spikes and inhibitory functions are introduced into spiking neural P systems based on the min-sequentiality strategy. We construct two sequential spiking neural P systems with anti-spikes in different ways. The corresponding modules of the two systems are designed separately. Finally, we prove that the two spiking neural P systems with anti-spikes based on the min-sequentiality strategy are universal as both number generators and acceptors.

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Acknowledgments

This work was supported by Anhui Provincial Natural Science Foundation (1808085MF173), and Natural Science Key Research Project for Higher Education Institutions of Anhui Province (KJ2017A942).

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Correspondence to Keqin Jiang .

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Li, L., Jiang, K. (2018). Spiking Neural P Systems with Anti-spikes Based on the Min-Sequentiality Strategy. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 951. Springer, Singapore. https://doi.org/10.1007/978-981-13-2826-8_9

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  • DOI: https://doi.org/10.1007/978-981-13-2826-8_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2825-1

  • Online ISBN: 978-981-13-2826-8

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