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Simplified and Yet Turing Universal Spiking Neural P Systems with Communication on Request
Tingfang Wu1, Florin-Daniel Bîlbîe2, Andrei Păun2,3
11 Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China.
International Journal of Neural Systems
|May 16, 2018
Summary
Spiking neural P systems (SNQ P systems) with one spike type are Turing universal. This finding simplifies previous models and confirms computational power in generating and accepting modes.
Area of Science:
- Membrane computing
- Computational neuroscience
- Artificial intelligence
Background:
- Spiking neural P systems (SNQ P systems) are a third-generation neural network model.
- Previous work established Turing universality for SNQ P systems using two spike types.
- This study focuses on a simplified SNQ P system variant.
Purpose of the Study:
- To investigate the computational power of SNQ P systems with only one type of spike.
- To determine if one spike type is sufficient for Turing universality.
- To analyze the impact of unbounded neurons on computational capacity.
Main Methods:
- Theoretical analysis of SNQ P systems with one spike type.
- Examination of SNQ P systems in both generating and accepting computational modes.
- Investigation into the role of the number of unbounded neurons.
Main Results:
- SNQ P systems with one type of spike are Turing universal.
- Universality is maintained in both number generating and accepting modes.
- Four unbounded neurons are sufficient for Turing universality in generating SNQ P systems.
Conclusions:
- One spike type is sufficient for Turing universality in SNQ P systems.
- The computational power of SNQ P systems is robust to simplification.
- Further research can explore optimized configurations for specific computational tasks.
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