Time After Time: Notes on Delays In Spiking Neural P Systems

TL;DR

This paper investigates how SNP systems with delays can be simulated by SNP systems without delays, focusing on various spike routing constructs such as sequential, iteration, join, and split.

Contribution

It provides methods to simulate delayed SNP systems using non-delayed ones for key spike routing constructs, enhancing understanding of their computational equivalence.

Findings

Delayed SNP systems can be simulated by non-delayed systems for key constructs

Simulation preserves computational capabilities of SNP systems

Enhances understanding of timing and routing in neural-inspired computing

Abstract

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.