Time After Time: Notes on Delays In Spiking Neural P Systems
This work addresses a theoretical problem in computational models for researchers in membrane computing, but it is incremental as it builds on existing Turing-complete variants.
The paper tackled the problem of simulating restricted forms of Spiking Neural P systems with delays using systems without delays, focusing on spike routing constructs like sequential, iteration, join, and split, and demonstrated these simulations.
Spiking Neural P systems, SNP systems for short, are biologically inspired computing devices based on how neurons perform computations. SNP systems use only one type of symbol, the spike, in the computations. Information is encoded in the time differences of spikes or the multiplicity of spikes produced at certain times. SNP systems with delays (associated with rules) and those without delays are two of several Turing complete SNP system variants in literature. In this work we investigate how restricted forms of SNP systems with delays can be simulated by SNP systems without delays. We show the simulations for the following spike routing constructs: sequential, iteration, join, and split.