Free choice Petri nets
Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems
Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Spiking neural P systems with extended rules: universality and languages
Natural Computing: an international journal
Hebbian Learning from Spiking Neural P Systems View
Membrane Computing
The Oxford Handbook of Membrane Computing
The Oxford Handbook of Membrane Computing
Matrix representation of spiking neural P systems
CMC'10 Proceedings of the 11th international conference on Membrane computing
P systems, petri nets, and program machines
WMC'05 Proceedings of the 6th international conference on Membrane Computing
Towards a petri net semantics for membrane systems
WMC'05 Proceedings of the 6th international conference on Membrane Computing
A spiking neural p system simulator based on CUDA
CMC'11 Proceedings of the 12th international conference on Membrane Computing
Fundamenta Informaticae
| Hi-index | 0.00 |
In this work we investigate further the relationship between Petri nets and Spiking Neural P (SNP) systems: we consider SNP systems that have source (no incoming synapse) and sink (no outgoing synapse) neurons, and the initial configuration of the system is where only the source neuron has only one spike. We then route the initial single spike through the system to the sink neuron, using routing constructs. This type of SNP systems are similar to Petri nets, in particular to Workflow (WF) nets. We observe structural and behavioral properties of these nets for routing a single token can be simulated by SNP systems with source and sink neurons. Certain routing types such as AND-splits and OR-joins are 'natural' in SNP systems, but AND-joins and especially OR-splits seem to be more complex. Our results also suggest the possibility of analysing workflows using SNP systems.