Abstract
This paper is an attempt to relax the condition of using the rules in a maximally parallel manner in the framework of spiking neural P systems with exhaustive use of rules. To this aim, we consider the minimal parallelism of using rules: if one rule associated with a neuron can be used, then the rule must be used at least once (but we do not care how many times). In this framework, we study the computational power of our systems as number generating devices. Weak as it might look, this minimal parallelism still leads to universality, even when we eliminate the delay between firing and spiking and the forgetting rules at the same time.
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This work was supported by National Natural Science Foundation of China (61502063).
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Jiang, Y., Luo, F., Luo, Y. (2017). Spiking Neural P Systems with Minimal Parallelism. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_10
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DOI: https://doi.org/10.1007/978-981-10-7179-9_10
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