1. The computation power of spiking neural P systems with polarizations adopting sequential mode induced by minimum spike number
- Author
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Linqiang Pan and Tingfang Wu
- Subjects
0209 industrial biotechnology ,Quantitative Biology::Neurons and Cognition ,Computer science ,Cognitive Neuroscience ,Computation ,02 engineering and technology ,Topology ,Computer Science Applications ,020901 industrial engineering & automation ,Models of neural computation ,Membrane ,medicine.anatomical_structure ,Polarized cell ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,020201 artificial intelligence & image processing ,Neuron ,Membrane computing ,P system - Abstract
Spiking neural P systems (SN P systems) refer to a type of distributed parallel neural computation model in the membrane computing framework. In this work, a new type of SN P system is examined, i.e., spiking neural P systems with polarizations (PSN P systems), by taking inspiration from the polarized cell membrane of a neuron. For the PSN P system, the firing condition of rules is the neuron-associated polarization. This work focuses on examining the computation power of the PSN P systems adopting the sequential mode induced by the minimum spike number, where at a computation step, one (resp., all) of neurons that hold the minimum spike number within the neurons which can fire will fire, i.e., the min-sequentiality strategy (resp., min-pseudo-sequentiality strategy). We prove that PSN P systems adopting the min-sequentiality strategy or min-pseudo-sequentiality strategy are Turing universal as the number generating devices. These results indicate the computation power of PSN P systems is robust regarding their strategies of sequentiality.
- Published
- 2020