@article {1914,
	title = {Notes on Spiking Neural P systems and finite automata},
	journal = {Thirteenth Brainstorming Week on Membrane Computing},
	year = {2015},
	month = {02/2015},
	pages = {77-89},
	publisher = {F{\'e}nix Editora},
	address = {Sevilla, Espa{\~n}a},
	abstract = {Spiking neural P systems (in short, SNP systems) are membrane computing
models inspired by the pulse coding of information in biological neurons. SNP systems
with standard rules have neurons that emit at most one spike (the pulse) each step, and
have either an input or output neuron connected to the environment. SNP transducers
were introduced, where both input and output neurons were used. More recently, SNP
modules were introduced which generalize SNP transducers: extended rules are used
(more than one spike can be emitted each step) and a set of input and output neurons can
be used. In this work we continue relating SNP modules and finite automata: (i) we amend
previous constructions for DFA and DFST simulations, (ii) improve the construction
from three neurons down to one neuron, (iii) DFA with output are simulated, and (iv)
we generate automatic sequences using results from (iii).},
	keywords = {Automatic sequences, finite automata, Membrane computing, spiking neural P systems},
	url = {http://www.cs.us.es/~marper/investigacion/proceedings-13th-BWMC.pdf},
	author = {Francis G. C. Cabarle and Henry N. Adorna and Mario J. P{\'e}rez-Jim{\'e}nez}
}
