Asynchronous Spiking Neural P Systems with Multiple Channels and Symbols
| Autor: | Hong Peng, Zeqiong Lv, Xiaoxiao Song, Jun Wang, Wenmei Yi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Theoretical computer science
Computer science 68Q10 General Engineering Process (computing) spiking neural P systems Class (philosophy) Type (model theory) multiple channels Mode (computer interface) Asynchronous communication Membrane computing asynchronous systems Completeness (statistics) Turing universality Turing computer multiple symbols computer.programming_language |
| Zdroj: | COMPUTING AND INFORMATICS; Vol. 39 No. 5 (2020): Computing and Informatics; 925–951 |
| ISSN: | 1335-9150 2585-8807 |
| Popis: | Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computation systems, inspired from the way that the neurons process and communicate information by means of spikes. A new variant of SNP systems, which works in asynchronous mode, asynchronous spiking neural P systems with multiple channels and symbols (ASNP-MCS systems, in short), is investigated in this paper. There are two interesting features in ASNP-MCS systems: multiple channels and multiple symbols. That is, every neuron has more than one synaptic channels to connect its subsequent neurons, and every neuron can deal with more than one type of spikes. The variant works in asynchronous mode: in every step, each neuron can be free to fire or not when its rules can be applied. The computational completeness of ASNP-MCS systems is investigated. It is proved that ASNP-MCS systems as number generating and accepting devices are Turing universal. Moreover, we obtain a small universal function computing device that is an ASNP-MCS system with 67 neurons. Specially, a new idea that can solve ``block'' problems is proposed in INPUT modules. |
| Databáze: | OpenAIRE |
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